setwd("C:/Work Files/Collaborations/Andi RAPD Project")RAPD Student Data
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expand, pack, unpackStudent_Data <- read_dta("Eisman_final_N346_8.8.24.dta")
write.csv(Student_Data, "Student_Data.csv")
Student_Data_V2 <- read.csv("Student_Data.csv")
Student_Data_Full <- read.csv("Student_Data_Full.csv")
names(Student_Data) [1] "studyid" "id1"
[3] "id2" "id3"
[5] "school" "XXXXXXXX_GROUP_DEMOS_XXXXXXXXXX"
[7] "rapd" "age_yrs_t1"
[9] "age_yrs_t2" "ethnicity"
[11] "race" "gender"
[13] "socialneed" "fuzzy"
[15] "XXXXXXXXX_OUTCOMES_XXXXXXXXXXX" "XXXXXXX_PRETEST_XXXXXXXXX"
[17] "attalc_t1" "attcig_t1"
[19] "atttob_t1" "attnic_t1"
[21] "attmj_t1" "peertob_t1"
[23] "peeralc_t1" "peermj_t1"
[25] "peerscrip_t1" "rsk1_t1"
[27] "rsk2_t1" "rsk3_t1"
[29] "rsk4_t1" "rsk5_t1"
[31] "rsk6_t1" "usevap_t1"
[33] "usealc_t1" "usemj_t1"
[35] "usescrip_t1" "usepk_t1"
[37] "usedrg_t1" "othdrug_t1"
[39] "usevap1_t1" "usealc1_t1"
[41] "usemj1_t1" "usescrip1_t1"
[43] "usepk1_t1" "usedrg1_t1"
[45] "knovap_t1" "knonic_t1"
[47] "knoscrip_t1" "knodrg_t1"
[49] "knomj_t1" "phq1_t1"
[51] "phq2_t1" "decmk1_t1"
[53] "decmk2_t1" "decmk3_t1"
[55] "assert1_t1" "assert2_t1"
[57] "assert3_t1" "assert4_t1"
[59] "infoseek1_t1" "realinfo1_t1"
[61] "profhelp1_t1" "emoe1_t1"
[63] "emoe2_t1" "emoe3_t1"
[65] "rsvap1_t1" "rsvap2_t1"
[67] "rsvap3_t1" "rsvap4_t1"
[69] "rsvap5_t1" "rsmj1_t1"
[71] "rsmj2_t1" "rsmj3_t1"
[73] "rsmj4_t1" "rsmj5_t1"
[75] "rsalc1_t1" "rsalc2_t1"
[77] "rsalc3_t1" "rsalc4_t1"
[79] "rsalc5_t1" "live_t1"
[81] "food1_t1" "food2_t1"
[83] "trans_t1" "perrisk1_t1"
[85] "perrisk2_t1" "perrisk3_t1"
[87] "perrisk4_t1" "interact1_t1"
[89] "interact2_t1" "interact3_t1"
[91] "interact4_t1" "problem_t1"
[93] "rspct1_t1" "rspct2_t1"
[95] "rspct3_t1" "rspct4_t1"
[97] "rspct5_t1" "rspct6_t1"
[99] "cope1_t1" "cope2_t1"
[101] "cope3_t1" "cope4_t1"
[103] "cope5_t1" "cope6_t1"
[105] "cope7_t1" "cope8_t1"
[107] "cope9_t1" "gad1_t1"
[109] "gad2_t1" "usevap_t1_d"
[111] "usealc_t1_d" "usemj_t1_d"
[113] "usescrip_t1_d" "usepk_t1_d"
[115] "usedrg_t1_d" "usevap1_t1_d"
[117] "usealc1_t1_d" "usemj1_t1_d"
[119] "usescrip1_t1_d" "usepk1_t1_d"
[121] "usedrg1_t1_d" "ref_vap_t1"
[123] "ref_mj_t1" "ref_alc_t1"
[125] "kno_sum_t1" "phq_sum_t1"
[127] "phq_dep_t1" "gad_sum_t1"
[129] "gad_anx_t1" "decmk_mean_t1"
[131] "assert_mean_t1" "suminteract_t1"
[133] "sumrespect_t1" "int_total_t1"
[135] "copepos_t1" "copeneg_t1"
[137] "XXXXXXX_POSTTEST_XXXXXXXXX" "attalc_t2"
[139] "attcig_t2" "atttob_t2"
[141] "attnic_t2" "attmj_t2"
[143] "peertob_t2" "peeralc_t2"
[145] "peermj_t2" "peerscrip_t2"
[147] "rsk1_t2" "rsk2_t2"
[149] "rsk3_t2" "rsk4_t2"
[151] "rsk5_t2" "rsk6_t2"
[153] "usevap1_t2" "usealc1_t2"
[155] "usemj1_t2" "usescrip1_t2"
[157] "usepk1_t2" "usedrg1_t2"
[159] "othdrg1_t2" "knovap_t2"
[161] "knonic_t2" "knoscrip_t2"
[163] "knodrg_t2" "knomj_t2"
[165] "phq1_t2" "phq2_t2"
[167] "decmk1_t2" "decmk2_t2"
[169] "decmk3_t2" "assert1_t2"
[171] "assert2_t2" "assert3_t2"
[173] "assert4_t2" "infoseek1_t2"
[175] "realinfo1_t2" "profhelp1_t2_0"
[177] "aim1_t2" "iam1_t2"
[179] "emoe1_t2" "emoe4_t2"
[181] "iam2_t2" "aim3_t2"
[183] "iam3_t2" "rsvap1_t2"
[185] "rsvap2_t2" "rsvap3_t2"
[187] "rsvap4_t2" "rsvap5_t2"
[189] "rsmj1_t2" "rsmj2_t2"
[191] "rsmj3_t2" "rsmj4_t2"
[193] "rsmj5_t2" "rsalc1_t2"
[195] "rsalc2_t2" "rsalc3_t2"
[197] "rsalc4_t2" "rsalc5_t2"
[199] "gad1_t2" "gad2_t2"
[201] "cope1_t2" "cope2_t2"
[203] "cope3_t2" "cope4_t2"
[205] "cope5_t2" "cope6_t2"
[207] "cope7_t2" "cope8_t2"
[209] "cope9_t2" "interact1_t2"
[211] "interact2_t2" "interact3_t2"
[213] "interact4_t2" "problem_t2"
[215] "rspct1_t2" "rspct2_t2"
[217] "rspct3_t2" "rspct4_t2"
[219] "rspct5_t2" "rspct6_t2"
[221] "perrisk1_t2" "perrisk2_t2"
[223] "perrisk3_t2" "perrisk4_t2"
[225] "usevap1_t2_d" "usealc1_t2_d"
[227] "usemj1_t2_d" "usescrip1_t2_d"
[229] "usepk1_t2_d" "usedrg1_t2_d"
[231] "decmk_mean_t2" "ref_vap_t2"
[233] "ref_mj_t2" "ref_alc_t2"
[235] "copepos_t2" "copeneg_t2"
[237] "kno_sum_t2" "phq_sum_t2"
[239] "phq_dep_t2" "gad_sum_t2"
[241] "gad_anx_t2" "assert_mean_t2"
[243] "suminteract_t2" "sumrespect_t2"
[245] "int_total_t2" "XXXXXXX_MISCELLANEOUS_XXXXXXXXX"
[247] "start_t1" "start_t2"
[249] "end_t1" "end_t2"
[251] "date_t1" "date_t2"
[253] "Assent" "control"
[255] "month_var" "semester"
[257] "Q1" "_merge"
[259] "nmiss" "date_only"
[261] "jan_15" "semester_v2"
[263] "rsk1_chg" "rsk2_chg"
[265] "rsk3_chg" "rsk4_chg"
[267] "rsk5_chg" "rsk6_chg"
[269] "emoe1_chg" "assert1_chg"
[271] "assert2_chg" "assert3_chg"
[273] "assert4_chg" "assert_mean_chg"
[275] "rsvap1_chg" "rsvap2_chg"
[277] "rsvap3_chg" "rsvap4_chg"
[279] "rsvap5_chg" "rsvap_mean_chg"
[281] "rsmj1_chg" "rsmj2_chg"
[283] "rsmj3_chg" "rsmj4_chg"
[285] "rsmj5_chg" "rsmj_mean_chg"
[287] "rsalc1_chg" "rsalc2_chg"
[289] "rsalc3_chg" "rsalc4_chg"
[291] "rsalc5_chg" "rsalc_mean_chg"
[293] "decmk1_chg" "decmk2_chg"
[295] "decmk3_chg" "decmk_mean_chg"
[297] "usealc1_chg" "usemj1_chg"
[299] "usescrip1_chg" "usepk1_chg"
[301] "usedrg1_chg" "usevap1_chg_d"
[303] "usealc1_chg_d" "usemj1_chg_d"
[305] "usescrip1_chg_d" "usepk1_chg_d"
[307] "usedrg1_chg_d" "usevap1_chg"
[309] "sociodis" "engagement_mean_t1"
[311] "engagement_mean_t2" "iam_mean"
[313] "aim_mean" "emoe_chg" table(Student_Data$race) # collapse White v. non-white
1 2 3 4 5 6 7 8
8 8 78 1 208 24 11 8 table(Student_Data$gender) # collapse male v. female & non-binary
1 2 3 4 5 6
181 155 2 4 3 1 table(Student_Data$socialneed)
0 1
296 50 table(Student_Data$gender,Student_Data$socialneed)
0 1
1 156 25
2 133 22
3 2 0
4 2 2
5 3 0
6 0 1table(Student_Data_V2$rapd)
0 1
54 292 table(Student_Data_V2$school)
1 4 5 6 10 11
78 34 20 107 33 74 null_model <- lmer(usealc1_t2 ~ 1 + (1 | school), data = Student_Data_V2, REML = TRUE)
variance_components <- as.data.frame(VarCorr(null_model))
school_variance <- variance_components$vcov[1] # Between-school variance
residual_variance <- variance_components$vcov[2] # Within-school (residual) variance
# Calculate ICC
ICC <- school_variance / (school_variance + residual_variance)
ICC[1] 0.007166019There are 292 Intervention Students and 54 control students and I need to add a weighting. I do need to impute the data for the treatment and controls separately, otherwise it will likely eliminate any treatment effects
Student_Data_V2_0 <- subset(Student_Data_V2, rapd == 0)
Student_Data_V2_1 <- subset(Student_Data_V2, rapd == 1)vars_for_imputation <- c("rapd","race", "gender", "usemj1_t1", "usemj1_t2", "attalc_t1", "attalc_t2", "attnic_t1", "attnic_t2", "attmj_t1", "attmj_t2", "knovap_t1", "knovap_t2", "knonic_t1", "knonic_t2", "knodrg_t1", "knodrg_t2", "knomj_t1", "knomj_t2", "peermj_t1", "peermj_t2", "peeralc_t1", "peeralc_t2", "perrisk2_t1", "perrisk2_t2", "perrisk3_t1", "perrisk3_t2", "rsk1_t1", "rsk1_t2", "rsk3_t1","rsk3_t2", "rsk4_t1","rsk4_t2","rsk5_t1","rsk5_t2","cope1_t1", "cope1_t2", "cope2_t1","cope2_t2","cope3_t1","cope3_t2", "cope4_t1", "cope4_t2", "cope5_t1", "cope5_t2","cope6_t1","cope6_t2", "cope7_t1", "cope7_t2", "cope8_t1","cope8_t2", "cope9_t1", "cope9_t2", "rsvap1_t1", "rsvap1_t2", "rsvap2_t1", "rsvap2_t2", "rsvap3_t1", "rsvap3_t2", "rsvap4_t1", "rsvap4_t2", "rsvap5_t1","rsvap5_t2","rsmj1_t1", "rsmj1_t2","rsmj2_t1", "rsmj2_t2", "rsmj3_t1","rsmj3_t2","rsmj4_t1","rsmj4_t2","rsmj5_t1", "rsmj5_t2", "rsalc1_t1","rsalc1_t2", "rsalc2_t1", "rsalc2_t2", "rsalc3_t1", "rsalc3_t2", "rsalc4_t1", "rsalc4_t2", "rsalc5_t1", "rsalc5_t2","usealc1_t1", "usealc1_t2", "usevap1_t1", "usevap1_t2", "phq1_t1","phq1_t2","phq2_t1", "phq2_t2", "gad1_t1", "gad1_t2", "gad2_t1","gad2_t2")
###Impute Data for the control group####
Student_Data_subset_0 <- Student_Data_V2_0[, vars_for_imputation]
imputed_data_0 <- mice(Student_Data_subset_0, m = 1, method = "pmm", seed = 123)
iter imp variable
1 1 usemj1_t1* usemj1_t2* attalc_t2* attnic_t2* attmj_t2* knovap_t1* knovap_t2* knonic_t1* knonic_t2* knodrg_t1* knodrg_t2* knomj_t1* knomj_t2* peermj_t1* peermj_t2* peeralc_t1* peeralc_t2* perrisk2_t1* perrisk2_t2* perrisk3_t1* perrisk3_t2* rsk1_t1* rsk1_t2* rsk3_t1* rsk3_t2* rsk4_t1* rsk4_t2* rsk5_t1* rsk5_t2* cope1_t1* cope1_t2* cope2_t1* cope2_t2* cope3_t1* cope3_t2* cope4_t1* cope4_t2* cope5_t1* cope5_t2* cope6_t1* cope6_t2* cope7_t1* cope7_t2* cope8_t1* cope8_t2* cope9_t1* cope9_t2* rsvap1_t1* rsvap1_t2* rsvap2_t1* rsvap2_t2* rsvap3_t1* rsvap3_t2* rsvap4_t1* rsvap4_t2* rsvap5_t1* rsvap5_t2* rsmj1_t1* rsmj1_t2* rsmj2_t1* rsmj2_t2* rsmj3_t1* rsmj3_t2* rsmj4_t1* rsmj4_t2* rsmj5_t1* rsmj5_t2* rsalc1_t1* rsalc1_t2* rsalc2_t1* rsalc2_t2* rsalc3_t1* rsalc3_t2* rsalc4_t1* rsalc4_t2* rsalc5_t1* rsalc5_t2* usealc1_t2* usevap1_t1* usevap1_t2* phq1_t1* phq1_t2* phq2_t1* phq2_t2* gad1_t1* gad1_t2* gad2_t1* gad2_t2*
2 1 usemj1_t1* usemj1_t2* attalc_t2* attnic_t2* attmj_t2* knovap_t1* knovap_t2* knonic_t1* knonic_t2* knodrg_t1* knodrg_t2* knomj_t1* knomj_t2* peermj_t1* peermj_t2* peeralc_t1* peeralc_t2* perrisk2_t1* perrisk2_t2* perrisk3_t1* perrisk3_t2* rsk1_t1* rsk1_t2* rsk3_t1* rsk3_t2* rsk4_t1* rsk4_t2* rsk5_t1* rsk5_t2* cope1_t1* cope1_t2* cope2_t1* cope2_t2* cope3_t1* cope3_t2* cope4_t1* cope4_t2* cope5_t1* cope5_t2* cope6_t1* cope6_t2* cope7_t1* cope7_t2* cope8_t1* cope8_t2* cope9_t1* cope9_t2* rsvap1_t1* rsvap1_t2* rsvap2_t1* rsvap2_t2* rsvap3_t1* rsvap3_t2* rsvap4_t1* rsvap4_t2* rsvap5_t1* rsvap5_t2* rsmj1_t1* rsmj1_t2* rsmj2_t1* rsmj2_t2* rsmj3_t1* rsmj3_t2* rsmj4_t1* rsmj4_t2* rsmj5_t1* rsmj5_t2* rsalc1_t1* rsalc1_t2* rsalc2_t1* rsalc2_t2* rsalc3_t1* rsalc3_t2* rsalc4_t1* rsalc4_t2* rsalc5_t1* rsalc5_t2* usealc1_t2* usevap1_t1* usevap1_t2* phq1_t1* phq1_t2* phq2_t1* phq2_t2* gad1_t1* gad1_t2* gad2_t1* gad2_t2*
3 1 usemj1_t1* usemj1_t2* attalc_t2* attnic_t2* attmj_t2* knovap_t1* knovap_t2* knonic_t1* knonic_t2* knodrg_t1* knodrg_t2* knomj_t1* knomj_t2* peermj_t1* peermj_t2* peeralc_t1* peeralc_t2* perrisk2_t1* perrisk2_t2* perrisk3_t1* perrisk3_t2* rsk1_t1* rsk1_t2* rsk3_t1* rsk3_t2* rsk4_t1* rsk4_t2* rsk5_t1* rsk5_t2* cope1_t1* cope1_t2* cope2_t1* cope2_t2* cope3_t1* cope3_t2* cope4_t1* cope4_t2* cope5_t1* cope5_t2* cope6_t1* cope6_t2* cope7_t1* cope7_t2* cope8_t1* cope8_t2* cope9_t1* cope9_t2* rsvap1_t1* rsvap1_t2* rsvap2_t1* rsvap2_t2* rsvap3_t1* rsvap3_t2* rsvap4_t1* rsvap4_t2* rsvap5_t1* rsvap5_t2* rsmj1_t1* rsmj1_t2* rsmj2_t1* rsmj2_t2* rsmj3_t1* rsmj3_t2* rsmj4_t1* rsmj4_t2* rsmj5_t1* rsmj5_t2* rsalc1_t1* rsalc1_t2* rsalc2_t1* rsalc2_t2* rsalc3_t1* rsalc3_t2* rsalc4_t1* rsalc4_t2* rsalc5_t1* rsalc5_t2* usealc1_t2* usevap1_t1* usevap1_t2* phq1_t1* phq1_t2* phq2_t1* phq2_t2* gad1_t1* gad1_t2* gad2_t1* gad2_t2*
4 1 usemj1_t1* usemj1_t2* attalc_t2* attnic_t2* attmj_t2* knovap_t1* knovap_t2* knonic_t1* knonic_t2* knodrg_t1* knodrg_t2* knomj_t1* knomj_t2* peermj_t1* peermj_t2* peeralc_t1* peeralc_t2* perrisk2_t1* perrisk2_t2* perrisk3_t1* perrisk3_t2* rsk1_t1* rsk1_t2* rsk3_t1* rsk3_t2* rsk4_t1* rsk4_t2* rsk5_t1* rsk5_t2* cope1_t1* cope1_t2* cope2_t1* cope2_t2* cope3_t1* cope3_t2* cope4_t1* cope4_t2* cope5_t1* cope5_t2* cope6_t1* cope6_t2* cope7_t1* cope7_t2* cope8_t1* cope8_t2* cope9_t1* cope9_t2* rsvap1_t1* rsvap1_t2* rsvap2_t1* rsvap2_t2* rsvap3_t1* rsvap3_t2* rsvap4_t1* rsvap4_t2* rsvap5_t1* rsvap5_t2* rsmj1_t1* rsmj1_t2* rsmj2_t1* rsmj2_t2* rsmj3_t1* rsmj3_t2* rsmj4_t1* rsmj4_t2* rsmj5_t1* rsmj5_t2* rsalc1_t1* rsalc1_t2* rsalc2_t1* rsalc2_t2* rsalc3_t1* rsalc3_t2* rsalc4_t1* rsalc4_t2* rsalc5_t1* rsalc5_t2* usealc1_t2* usevap1_t1* usevap1_t2* phq1_t1* phq1_t2* phq2_t1* phq2_t2* gad1_t1* gad1_t2* gad2_t1* gad2_t2*
5 1 usemj1_t1* usemj1_t2* attalc_t2* attnic_t2* attmj_t2* knovap_t1* knovap_t2* knonic_t1* knonic_t2* knodrg_t1* knodrg_t2* knomj_t1* knomj_t2* peermj_t1* peermj_t2* peeralc_t1* peeralc_t2* perrisk2_t1* perrisk2_t2* perrisk3_t1* perrisk3_t2* rsk1_t1* rsk1_t2* rsk3_t1* rsk3_t2* rsk4_t1* rsk4_t2* rsk5_t1* rsk5_t2* cope1_t1* cope1_t2* cope2_t1* cope2_t2* cope3_t1* cope3_t2* cope4_t1* cope4_t2* cope5_t1* cope5_t2* cope6_t1* cope6_t2* cope7_t1* cope7_t2* cope8_t1* cope8_t2* cope9_t1* cope9_t2* rsvap1_t1* rsvap1_t2* rsvap2_t1* rsvap2_t2* rsvap3_t1* rsvap3_t2* rsvap4_t1* rsvap4_t2* rsvap5_t1* rsvap5_t2* rsmj1_t1* rsmj1_t2* rsmj2_t1* rsmj2_t2* rsmj3_t1* rsmj3_t2* rsmj4_t1* rsmj4_t2* rsmj5_t1* rsmj5_t2* rsalc1_t1* rsalc1_t2* rsalc2_t1* rsalc2_t2* rsalc3_t1* rsalc3_t2* rsalc4_t1* rsalc4_t2* rsalc5_t1* rsalc5_t2* usealc1_t2* usevap1_t1* usevap1_t2* phq1_t1* phq1_t2* phq2_t1* phq2_t2* gad1_t1* gad1_t2* gad2_t1* gad2_t2*Warning: Number of logged events: 970summary(imputed_data_0)Class: mids
Number of multiple imputations: 1
Imputation methods:
rapd race gender usemj1_t1 usemj1_t2 attalc_t1
"" "" "" "pmm" "pmm" ""
attalc_t2 attnic_t1 attnic_t2 attmj_t1 attmj_t2 knovap_t1
"pmm" "" "pmm" "" "pmm" "pmm"
knovap_t2 knonic_t1 knonic_t2 knodrg_t1 knodrg_t2 knomj_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
knomj_t2 peermj_t1 peermj_t2 peeralc_t1 peeralc_t2 perrisk2_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2 rsk3_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
cope4_t2 cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2 rsmj5_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1
"pmm" "pmm" "pmm" "pmm" "pmm" ""
usealc1_t2 usevap1_t1 usevap1_t2 phq1_t1 phq1_t2 phq2_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
phq2_t2 gad1_t1 gad1_t2 gad2_t1 gad2_t2
"pmm" "pmm" "pmm" "pmm" "pmm"
PredictorMatrix:
rapd race gender usemj1_t1 usemj1_t2 attalc_t1 attalc_t2 attnic_t1
rapd 0 1 1 1 1 1 1 1
race 0 0 1 1 1 1 1 1
gender 0 1 0 1 1 1 1 1
usemj1_t1 0 1 1 0 1 1 1 1
usemj1_t2 0 1 1 1 0 1 1 1
attalc_t1 0 1 1 1 1 0 1 1
attnic_t2 attmj_t1 attmj_t2 knovap_t1 knovap_t2 knonic_t1 knonic_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1
rapd 1 1 1 1 1 1
race 1 1 1 1 1 1
gender 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1
rsk1_t2 rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1
rapd 1 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1 1
cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1 cope7_t2 cope8_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
cope8_t2 cope9_t1 cope9_t2 rsvap1_t1 rsvap1_t2 rsvap2_t1 rsvap2_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1
rapd 1 1 1 1 1 0
race 1 1 1 1 1 0
gender 1 1 1 1 1 0
usemj1_t1 1 1 1 1 1 0
usemj1_t2 1 1 1 1 1 0
attalc_t1 1 1 1 1 1 0
usealc1_t2 usevap1_t1 usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
gad1_t1 gad1_t2 gad2_t1 gad2_t2
rapd 1 1 1 1
race 1 1 1 1
gender 1 1 1 1
usemj1_t1 1 1 1 1
usemj1_t2 1 1 1 1
attalc_t1 1 1 1 1
Number of logged events: 970
it im dep meth
1 0 0 constant
2 0 0 collinear
3 1 1 usemj1_t1 pmm
4 1 1 usemj1_t1 pmm
5 1 1 usemj1_t1 pmm
6 1 1 usemj1_t2 pmm
out
1 rapd
2 usealc1_t1
3 df set to 1. # observed cases: 12 # predictors: 93
4 race, gender, attalc_t1, attalc_t2, attnic_t2, attmj_t1, attmj_t2, knovap_t1, knovap_t2, knonic_t1, knonic_t2, knodrg_t2, knomj_t1, knomj_t2, peermj_t2, perrisk2_t2, perrisk3_t1, perrisk3_t2, rsk1_t2, rsk4_t1, rsk4_t2, rsk5_t1, rsk5_t2, cope1_t1, cope2_t2, cope3_t1, cope4_t1, cope4_t2, cope5_t1, cope6_t1, cope7_t1, cope8_t2, cope9_t2, rsvap3_t2, rsvap4_t2, rsvap5_t2, rsmj1_t1, rsmj1_t2, rsmj2_t1, rsmj3_t1, rsmj5_t1, rsmj5_t2, rsalc2_t2, rsalc3_t1, rsalc3_t2, rsalc5_t2, usevap1_t1, usevap1_t2, phq2_t2, gad1_t1
5 mice detected that your data are (nearly) multi-collinear.\nIt applied a ridge penalty to continue calculations, but the results can be unstable.\nDoes your dataset contain duplicates, linear transformation, or factors with unique respondent names?
6 df set to 1. # observed cases: 51 # predictors: 93completed_data_0 <- complete(imputed_data_0, 1)
###Impute Data for the treatment group####
Student_Data_subset_1 <- Student_Data_V2_1[, vars_for_imputation]
imputed_data_1 <- mice(Student_Data_subset_1, m = 1, method = "pmm", seed = 123)
iter imp variable
1 1 usemj1_t1* usemj1_t2 attalc_t1 attnic_t1 attmj_t1 knovap_t1 knovap_t2 knonic_t1 knonic_t2 knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1 peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2 rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1 cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2 cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1 cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1 rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2 rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1 rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1* usealc1_t2 usevap1_t1* usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2 gad1_t1 gad1_t2 gad2_t1 gad2_t2
2 1 usemj1_t1* usemj1_t2 attalc_t1 attnic_t1 attmj_t1 knovap_t1 knovap_t2 knonic_t1 knonic_t2 knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1 peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2 rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1 cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2 cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1 cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1 rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2 rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1 rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1* usealc1_t2 usevap1_t1* usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2 gad1_t1 gad1_t2 gad2_t1 gad2_t2
3 1 usemj1_t1* usemj1_t2 attalc_t1 attnic_t1 attmj_t1 knovap_t1 knovap_t2 knonic_t1 knonic_t2 knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1 peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2 rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1 cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2 cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1 cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1 rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2 rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1 rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1* usealc1_t2 usevap1_t1* usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2 gad1_t1 gad1_t2 gad2_t1 gad2_t2
4 1 usemj1_t1* usemj1_t2 attalc_t1 attnic_t1 attmj_t1 knovap_t1 knovap_t2 knonic_t1 knonic_t2 knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1 peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2 rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1 cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2 cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1 cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1 rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2 rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1 rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1* usealc1_t2 usevap1_t1* usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2 gad1_t1 gad1_t2 gad2_t1 gad2_t2
5 1 usemj1_t1* usemj1_t2 attalc_t1 attnic_t1 attmj_t1 knovap_t1 knovap_t2 knonic_t1 knonic_t2 knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1 peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2 rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1 cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2 cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1 cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1 rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2 rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1 rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1* usealc1_t2 usevap1_t1* usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2 gad1_t1 gad1_t2 gad2_t1 gad2_t2Warning: Number of logged events: 78summary(imputed_data_1)Class: mids
Number of multiple imputations: 1
Imputation methods:
rapd race gender usemj1_t1 usemj1_t2 attalc_t1
"" "" "" "pmm" "pmm" "pmm"
attalc_t2 attnic_t1 attnic_t2 attmj_t1 attmj_t2 knovap_t1
"" "pmm" "" "pmm" "" "pmm"
knovap_t2 knonic_t1 knonic_t2 knodrg_t1 knodrg_t2 knomj_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
knomj_t2 peermj_t1 peermj_t2 peeralc_t1 peeralc_t2 perrisk2_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2 rsk3_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
cope4_t2 cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2 rsmj5_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
usealc1_t2 usevap1_t1 usevap1_t2 phq1_t1 phq1_t2 phq2_t1
"pmm" "pmm" "pmm" "pmm" "pmm" "pmm"
phq2_t2 gad1_t1 gad1_t2 gad2_t1 gad2_t2
"pmm" "pmm" "pmm" "pmm" "pmm"
PredictorMatrix:
rapd race gender usemj1_t1 usemj1_t2 attalc_t1 attalc_t2 attnic_t1
rapd 0 1 1 1 1 1 1 1
race 0 0 1 1 1 1 1 1
gender 0 1 0 1 1 1 1 1
usemj1_t1 0 1 1 0 1 1 1 1
usemj1_t2 0 1 1 1 0 1 1 1
attalc_t1 0 1 1 1 1 0 1 1
attnic_t2 attmj_t1 attmj_t2 knovap_t1 knovap_t2 knonic_t1 knonic_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1
rapd 1 1 1 1 1 1
race 1 1 1 1 1 1
gender 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1
rsk1_t2 rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1
rapd 1 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1 1
cope1_t2 cope2_t1 cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
cope5_t1 cope5_t2 cope6_t1 cope6_t2 cope7_t1 cope7_t2 cope8_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
cope8_t2 cope9_t1 cope9_t2 rsvap1_t1 rsvap1_t2 rsvap2_t1 rsvap2_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2 rsvap5_t1 rsvap5_t2 rsmj1_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2 rsmj4_t1 rsmj4_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2 rsalc3_t1
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t1
rapd 1 1 1 1 1 1
race 1 1 1 1 1 1
gender 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1
usealc1_t2 usevap1_t1 usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2
rapd 1 1 1 1 1 1 1
race 1 1 1 1 1 1 1
gender 1 1 1 1 1 1 1
usemj1_t1 1 1 1 1 1 1 1
usemj1_t2 1 1 1 1 1 1 1
attalc_t1 1 1 1 1 1 1 1
gad1_t1 gad1_t2 gad2_t1 gad2_t2
rapd 1 1 1 1
race 1 1 1 1
gender 1 1 1 1
usemj1_t1 1 1 1 1
usemj1_t2 1 1 1 1
attalc_t1 1 1 1 1
Number of logged events: 78
it im dep meth
1 0 0 constant
2 1 1 usemj1_t1 pmm
3 1 1 usemj1_t1 pmm
4 1 1 usemj1_t1 pmm
5 1 1 usealc1_t1 pmm
6 1 1 usealc1_t1 pmm
out
1 rapd
2 df set to 1. # observed cases: 21 # predictors: 94
3 race, gender, attalc_t1, attalc_t2, attmj_t2, knovap_t1, knovap_t2, knonic_t1, knonic_t2, knodrg_t1, knodrg_t2, peermj_t1, peeralc_t2, perrisk3_t2, rsk1_t1, rsk3_t1, rsk3_t2, rsk4_t1, rsk4_t2, rsk5_t1, rsk5_t2, cope1_t1, cope3_t2, cope4_t1, cope4_t2, cope5_t1, cope5_t2, cope6_t1, cope6_t2, cope7_t1, cope7_t2, cope8_t1, cope8_t2, cope9_t1, cope9_t2, rsvap1_t1, rsvap2_t1, rsvap2_t2, rsvap3_t1, rsvap3_t2, rsvap4_t2, rsmj1_t1, rsmj2_t2, rsmj3_t2, rsalc2_t1, rsalc2_t2, rsalc4_t2, rsalc5_t1, usealc1_t2, usevap1_t1
4 mice detected that your data are (nearly) multi-collinear.\nIt applied a ridge penalty to continue calculations, but the results can be unstable.\nDoes your dataset contain duplicates, linear transformation, or factors with unique respondent names?
5 df set to 1. # observed cases: 24 # predictors: 94
6 race, gender, usemj1_t1, attalc_t2, attmj_t1, attmj_t2, knovap_t2, knonic_t1, knonic_t2, knodrg_t1, knodrg_t2, knomj_t1, knomj_t2, peeralc_t2, perrisk3_t1, perrisk3_t2, rsk1_t2, rsk3_t1, rsk5_t1, rsk5_t2, cope1_t2, cope2_t2, cope3_t1, cope4_t1, cope4_t2, cope6_t2, cope7_t1, cope7_t2, cope9_t1, rsvap1_t1, rsvap1_t2, rsvap2_t1, rsvap2_t2, rsvap3_t1, rsvap3_t2, rsvap4_t1, rsmj1_t1, rsmj1_t2, rsmj3_t1, rsmj4_t1, rsmj5_t2, rsalc2_t1, rsalc4_t1, usevap1_t2completed_data_1 <- complete(imputed_data_1, 1)
Student_Data_Full <- rbind(completed_data_0, completed_data_1)
write.csv(Student_Data_Full,"Student_Data_Full.csv")
names(Student_Data_Full) [1] "rapd" "race" "gender" "usemj1_t1" "usemj1_t2"
[6] "attalc_t1" "attalc_t2" "attnic_t1" "attnic_t2" "attmj_t1"
[11] "attmj_t2" "knovap_t1" "knovap_t2" "knonic_t1" "knonic_t2"
[16] "knodrg_t1" "knodrg_t2" "knomj_t1" "knomj_t2" "peermj_t1"
[21] "peermj_t2" "peeralc_t1" "peeralc_t2" "perrisk2_t1" "perrisk2_t2"
[26] "perrisk3_t1" "perrisk3_t2" "rsk1_t1" "rsk1_t2" "rsk3_t1"
[31] "rsk3_t2" "rsk4_t1" "rsk4_t2" "rsk5_t1" "rsk5_t2"
[36] "cope1_t1" "cope1_t2" "cope2_t1" "cope2_t2" "cope3_t1"
[41] "cope3_t2" "cope4_t1" "cope4_t2" "cope5_t1" "cope5_t2"
[46] "cope6_t1" "cope6_t2" "cope7_t1" "cope7_t2" "cope8_t1"
[51] "cope8_t2" "cope9_t1" "cope9_t2" "rsvap1_t1" "rsvap1_t2"
[56] "rsvap2_t1" "rsvap2_t2" "rsvap3_t1" "rsvap3_t2" "rsvap4_t1"
[61] "rsvap4_t2" "rsvap5_t1" "rsvap5_t2" "rsmj1_t1" "rsmj1_t2"
[66] "rsmj2_t1" "rsmj2_t2" "rsmj3_t1" "rsmj3_t2" "rsmj4_t1"
[71] "rsmj4_t2" "rsmj5_t1" "rsmj5_t2" "rsalc1_t1" "rsalc1_t2"
[76] "rsalc2_t1" "rsalc2_t2" "rsalc3_t1" "rsalc3_t2" "rsalc4_t1"
[81] "rsalc4_t2" "rsalc5_t1" "rsalc5_t2" "usealc1_t1" "usealc1_t2"
[86] "usevap1_t1" "usevap1_t2" "phq1_t1" "phq1_t2" "phq2_t1"
[91] "phq2_t2" "gad1_t1" "gad1_t2" "gad2_t1" "gad2_t2" table(Student_Data_Full$race)
1 2 3 4 5 6 7 8
8 8 78 1 208 24 11 8 Student_Data_Full$male_binary <- ifelse(Student_Data_Full$gender == 1, 1, 0)
Student_Data_Full$male_binary <- factor(Student_Data_Full$male_binary,
levels = c(1, 0),
labels = c("male", "not male"))
table(Student_Data_Full$male_binary)
male not male
181 165 Student_Data_Full$White_binary <- ifelse(Student_Data_Full$race == 5,1,0)
Student_Data_Full$White_binary <- factor(Student_Data_Full$White_binary,
levels= c(1,0),
labels = c("White","not White"))
table(Student_Data_Full$White_binary)
White not White
208 138 library(ipw)
ps_model <- glm(rapd ~ ., family = binomial, data = Student_Data_Full)Warning: glm.fit: algorithm did not convergeWarning: glm.fit: fitted probabilities numerically 0 or 1 occurredsummary(ps_model)
Call:
glm(formula = rapd ~ ., family = binomial, data = Student_Data_Full)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 5.034e+01 1.044e+06 0 1
race -1.783e+00 4.707e+04 0 1
gender -5.864e+00 6.925e+04 0 1
usemj1_t1 1.376e+00 9.993e+04 0 1
usemj1_t2 -1.388e+01 2.089e+05 0 1
attalc_t1 1.856e+00 9.848e+04 0 1
attalc_t2 5.955e+00 9.013e+04 0 1
attnic_t1 -5.911e+00 1.086e+05 0 1
attnic_t2 5.651e+00 1.176e+05 0 1
attmj_t1 4.283e+00 8.973e+04 0 1
attmj_t2 -4.395e+00 1.121e+05 0 1
knovap_t1 3.329e+00 2.979e+05 0 1
knovap_t2 1.175e+01 4.511e+05 0 1
knonic_t1 2.210e+00 2.677e+05 0 1
knonic_t2 -1.214e+01 5.559e+05 0 1
knodrg_t1 6.246e+00 1.561e+05 0 1
knodrg_t2 -3.967e+00 1.140e+05 0 1
knomj_t1 1.919e+01 1.675e+05 0 1
knomj_t2 -2.879e+00 1.956e+05 0 1
peermj_t1 2.832e-01 1.432e+05 0 1
peermj_t2 7.256e+00 1.344e+05 0 1
peeralc_t1 6.620e+00 1.070e+05 0 1
peeralc_t2 -8.823e+00 1.513e+05 0 1
perrisk2_t1 1.109e+00 1.368e+05 0 1
perrisk2_t2 -1.626e+00 7.632e+04 0 1
perrisk3_t1 -3.922e+00 1.266e+05 0 1
perrisk3_t2 6.953e-01 1.145e+05 0 1
rsk1_t1 -7.386e+00 1.515e+05 0 1
rsk1_t2 -8.973e+00 1.402e+05 0 1
rsk3_t1 2.616e+00 8.602e+04 0 1
rsk3_t2 4.161e+00 1.142e+05 0 1
rsk4_t1 -9.400e-01 1.203e+05 0 1
rsk4_t2 -6.348e+00 1.078e+05 0 1
rsk5_t1 2.756e-01 1.354e+05 0 1
rsk5_t2 7.903e+00 1.716e+05 0 1
cope1_t1 -1.326e+00 7.859e+04 0 1
cope1_t2 2.280e+00 7.220e+04 0 1
cope2_t1 -1.257e+00 9.140e+04 0 1
cope2_t2 -2.398e+00 7.497e+04 0 1
cope3_t1 5.030e-03 8.631e+04 0 1
cope3_t2 -1.890e+00 8.673e+04 0 1
cope4_t1 -4.105e+00 7.213e+04 0 1
cope4_t2 -3.411e+00 1.134e+05 0 1
cope5_t1 7.315e+00 6.986e+04 0 1
cope5_t2 -6.230e+00 8.089e+04 0 1
cope6_t1 4.888e-01 1.211e+05 0 1
cope6_t2 -5.280e+00 8.822e+04 0 1
cope7_t1 -9.674e+00 1.097e+05 0 1
cope7_t2 4.777e+00 7.497e+04 0 1
cope8_t1 -1.022e+00 8.279e+04 0 1
cope8_t2 -3.523e+00 7.900e+04 0 1
cope9_t1 1.306e+00 8.149e+04 0 1
cope9_t2 7.329e+00 8.419e+04 0 1
rsvap1_t1 1.959e+01 1.585e+05 0 1
rsvap1_t2 1.721e+01 2.208e+05 0 1
rsvap2_t1 -1.133e-02 1.415e+05 0 1
rsvap2_t2 1.184e+00 1.441e+05 0 1
rsvap3_t1 2.331e+00 1.640e+05 0 1
rsvap3_t2 1.032e+00 1.250e+05 0 1
rsvap4_t1 -1.423e+01 2.157e+05 0 1
rsvap4_t2 -6.983e+00 1.487e+05 0 1
rsvap5_t1 1.410e-02 1.215e+05 0 1
rsvap5_t2 8.134e+00 9.186e+04 0 1
rsmj1_t1 -8.273e+00 1.371e+05 0 1
rsmj1_t2 -6.430e+00 1.474e+05 0 1
rsmj2_t1 -6.090e+00 1.415e+05 0 1
rsmj2_t2 -3.293e+00 1.490e+05 0 1
rsmj3_t1 5.584e+00 1.861e+05 0 1
rsmj3_t2 1.771e+01 1.440e+05 0 1
rsmj4_t1 7.820e+00 1.220e+05 0 1
rsmj4_t2 -1.063e+01 1.558e+05 0 1
rsmj5_t1 -9.517e+00 1.351e+05 0 1
rsmj5_t2 -5.924e+00 1.690e+05 0 1
rsalc1_t1 -2.319e+01 1.747e+05 0 1
rsalc1_t2 -1.203e+00 1.974e+05 0 1
rsalc2_t1 3.949e+00 1.961e+05 0 1
rsalc2_t2 8.373e+00 1.282e+05 0 1
rsalc3_t1 -5.722e+00 1.889e+05 0 1
rsalc3_t2 -1.245e+01 1.666e+05 0 1
rsalc4_t1 1.434e+01 1.851e+05 0 1
rsalc4_t2 6.816e+00 2.332e+05 0 1
rsalc5_t1 8.713e+00 1.145e+05 0 1
rsalc5_t2 -7.237e+00 1.683e+05 0 1
usealc1_t1 -3.764e+00 8.266e+04 0 1
usealc1_t2 7.281e+00 1.912e+05 0 1
usevap1_t1 -6.529e-01 5.717e+04 0 1
usevap1_t2 4.000e+00 2.091e+05 0 1
phq1_t1 -3.857e-01 1.093e+05 0 1
phq1_t2 -4.984e-01 1.451e+05 0 1
phq2_t1 4.219e+00 1.003e+05 0 1
phq2_t2 5.908e+00 1.513e+05 0 1
gad1_t1 6.425e+00 1.091e+05 0 1
gad1_t2 -2.405e+00 1.082e+05 0 1
gad2_t1 3.339e-01 1.005e+05 0 1
gad2_t2 -4.964e+00 9.802e+04 0 1
male_binarynot male 6.451e+00 1.399e+05 0 1
White_binarynot White -6.527e+00 1.073e+05 0 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 9.4544e+01 on 302 degrees of freedom
Residual deviance: 3.2844e-09 on 206 degrees of freedom
(43 observations deleted due to missingness)
AIC: 194
Number of Fisher Scoring iterations: 25Student_Data_Full$propensity_score <- predict(ps_model, newdata = Student_Data_Full, type = "response")
# Calculate inverse probability weights
Student_Data_Full$ipw <- ifelse(Student_Data_Full$rapd == 1,
1 / Student_Data_Full$propensity_score,
1 / (1 - Student_Data_Full$propensity_score))
hist(Student_Data_Full$ipw)
sum(is.na(Student_Data_Full$ipw))[1] 43md.pattern(Student_Data_Full)
rapd race gender usemj1_t1 usemj1_t2 attalc_t1 attalc_t2 attnic_t1
303 1 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0
attnic_t2 attmj_t1 attmj_t2 knovap_t1 knovap_t2 knonic_t1 knonic_t2
303 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1
0 0 0 0 0 0 0
knodrg_t1 knodrg_t2 knomj_t1 knomj_t2 peermj_t1 peermj_t2 peeralc_t1
303 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1
0 0 0 0 0 0 0
peeralc_t2 perrisk2_t1 perrisk2_t2 perrisk3_t1 perrisk3_t2 rsk1_t1 rsk1_t2
303 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1
0 0 0 0 0 0 0
rsk3_t1 rsk3_t2 rsk4_t1 rsk4_t2 rsk5_t1 rsk5_t2 cope1_t1 cope1_t2 cope2_t1
303 1 1 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0 0
cope2_t2 cope3_t1 cope3_t2 cope4_t1 cope4_t2 cope5_t1 cope5_t2 cope6_t1
303 1 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0
cope6_t2 cope7_t1 cope7_t2 cope8_t1 cope8_t2 cope9_t1 cope9_t2 rsvap1_t1
303 1 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0
rsvap1_t2 rsvap2_t1 rsvap2_t2 rsvap3_t1 rsvap3_t2 rsvap4_t1 rsvap4_t2
303 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1
0 0 0 0 0 0 0
rsvap5_t1 rsvap5_t2 rsmj1_t1 rsmj1_t2 rsmj2_t1 rsmj2_t2 rsmj3_t1 rsmj3_t2
303 1 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0
rsmj4_t1 rsmj4_t2 rsmj5_t1 rsmj5_t2 rsalc1_t1 rsalc1_t2 rsalc2_t1 rsalc2_t2
303 1 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0
rsalc3_t1 rsalc3_t2 rsalc4_t1 rsalc4_t2 rsalc5_t1 rsalc5_t2 usealc1_t2
303 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1
0 0 0 0 0 0 0
usevap1_t1 usevap1_t2 phq1_t1 phq1_t2 phq2_t1 phq2_t2 gad1_t1 gad1_t2
303 1 1 1 1 1 1 1 1
43 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0
gad2_t1 gad2_t2 male_binary White_binary usealc1_t1 propensity_score ipw
303 1 1 1 1 1 1 1
43 1 1 1 1 0 0 0
0 0 0 0 43 43 43
303 0
43 3
129Student_Data_Full_No_NA<- Student_Data_Full[!is.na(Student_Data_Full$ipw), ]
names(Student_Data_Full_No_NA) [1] "rapd" "race" "gender" "usemj1_t1"
[5] "usemj1_t2" "attalc_t1" "attalc_t2" "attnic_t1"
[9] "attnic_t2" "attmj_t1" "attmj_t2" "knovap_t1"
[13] "knovap_t2" "knonic_t1" "knonic_t2" "knodrg_t1"
[17] "knodrg_t2" "knomj_t1" "knomj_t2" "peermj_t1"
[21] "peermj_t2" "peeralc_t1" "peeralc_t2" "perrisk2_t1"
[25] "perrisk2_t2" "perrisk3_t1" "perrisk3_t2" "rsk1_t1"
[29] "rsk1_t2" "rsk3_t1" "rsk3_t2" "rsk4_t1"
[33] "rsk4_t2" "rsk5_t1" "rsk5_t2" "cope1_t1"
[37] "cope1_t2" "cope2_t1" "cope2_t2" "cope3_t1"
[41] "cope3_t2" "cope4_t1" "cope4_t2" "cope5_t1"
[45] "cope5_t2" "cope6_t1" "cope6_t2" "cope7_t1"
[49] "cope7_t2" "cope8_t1" "cope8_t2" "cope9_t1"
[53] "cope9_t2" "rsvap1_t1" "rsvap1_t2" "rsvap2_t1"
[57] "rsvap2_t2" "rsvap3_t1" "rsvap3_t2" "rsvap4_t1"
[61] "rsvap4_t2" "rsvap5_t1" "rsvap5_t2" "rsmj1_t1"
[65] "rsmj1_t2" "rsmj2_t1" "rsmj2_t2" "rsmj3_t1"
[69] "rsmj3_t2" "rsmj4_t1" "rsmj4_t2" "rsmj5_t1"
[73] "rsmj5_t2" "rsalc1_t1" "rsalc1_t2" "rsalc2_t1"
[77] "rsalc2_t2" "rsalc3_t1" "rsalc3_t2" "rsalc4_t1"
[81] "rsalc4_t2" "rsalc5_t1" "rsalc5_t2" "usealc1_t1"
[85] "usealc1_t2" "usevap1_t1" "usevap1_t2" "phq1_t1"
[89] "phq1_t2" "phq2_t1" "phq2_t2" "gad1_t1"
[93] "gad1_t2" "gad2_t1" "gad2_t2" "male_binary"
[97] "White_binary" "propensity_score" "ipw" Full model for marijuana use with weights
MJ_Full <- '
##Latent Variables##
coping_t1 =~ cope1_t1 + cope2_t1 + cope3_t1 + cope4_t1 + cope5_t1 +
cope6_t1 + cope7_t1 + cope8_t1 + cope9_t1
coping_t2 =~ cope1_t2 + cope2_t2 + cope3_t2 + cope4_t2 + cope5_t2 +
cope6_t2 + cope7_t2 + cope8_t2 + cope9_t2
Refusal_t1 =~ rsmj1_t1 + rsmj2_t1 + rsmj3_t1 + rsmj4_t1 + rsmj5_t1
Refusal_t2 =~ rsmj1_t2 + rsmj2_t2 + rsmj3_t2 + rsmj4_t2 + rsmj5_t2
##Regressions
attmj_t2 ~ attmj_t1
peermj_t2 ~ peermj_t1
knomj_t2 ~ knomj_t1
rsk5_t2 ~ rsk5_t1
coping_t2 ~ coping_t1
Refusal_t2 ~ Refusal_t1
usemj1_t2 ~ usemj1_t1 +coping_t2 + Refusal_t2 + knomj_t2 + rsk5_t2 +
peermj_t2 + attmj_t2 + rapd
coping_t2 ~ rapd
Refusal_t2 ~ rapd
knomj_t2 ~ rapd
rsk5_t2 ~ rapd
peermj_t2 ~ rapd
attmj_t2 ~ rapd
###Model Updates##
rsmj1_t1 ~~ rsmj4_t1
peermj_t2 ~~ attmj_t2
rsmj1_t2 ~~ rsmj4_t2
Refusal_t1 ~~ peermj_t1
peermj_t1 ~~ attmj_t1
cope2_t1 ~~ cope2_t2
cope2_t1 ~~ cope6_t1
cope5_t2 ~~ cope7_t2
cope2_t1 ~~ rsk5_t2
'
MJ_Full_fit <- sem(MJ_Full, data = Student_Data_Full_No_NA, estimator = "mlr",
sampling.weights = "ipw",
mimic = "Mplus")
summary(MJ_Full_fit, fit.measures = TRUE)lavaan 0.6-19 ended normally after 180 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 128
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 2350.439 2127.495
Degrees of freedom 677 677
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.105
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 5375.321 4659.955
Degrees of freedom 735 735
P-value 0.000 0.000
Scaling correction factor 1.154
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.639 0.630
Tucker-Lewis Index (TLI) 0.608 0.599
Robust Comparative Fit Index (CFI) 0.651
Robust Tucker-Lewis Index (TLI) 0.621
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -13366.319 -13366.319
Scaling correction factor 1.344
for the MLR correction
Loglikelihood unrestricted model (H1) -12191.099 -12191.099
Scaling correction factor 1.143
for the MLR correction
Akaike (AIC) 26988.638 26988.638
Bayesian (BIC) 27463.995 27463.995
Sample-size adjusted Bayesian (SABIC) 27058.047 27058.047
Root Mean Square Error of Approximation:
RMSEA 0.090 0.084
90 Percent confidence interval - lower 0.086 0.080
90 Percent confidence interval - upper 0.094 0.088
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 0.961
Robust RMSEA 0.088
90 Percent confidence interval - lower 0.084
90 Percent confidence interval - upper 0.092
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.999
Standardized Root Mean Square Residual:
SRMR 0.133 0.133
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|)
coping_t1 =~
cope1_t1 1.000
cope2_t1 -1.340 1.991 -0.673 0.501
cope3_t1 4.299 3.274 1.313 0.189
cope4_t1 1.334 0.726 1.837 0.066
cope5_t1 0.646 1.404 0.460 0.645
cope6_t1 3.215 2.682 1.198 0.231
cope7_t1 -0.702 1.552 -0.452 0.651
cope8_t1 2.934 2.294 1.279 0.201
cope9_t1 -0.151 0.886 -0.170 0.865
coping_t2 =~
cope1_t2 1.000
cope2_t2 0.275 0.176 1.566 0.117
cope3_t2 1.559 0.265 5.892 0.000
cope4_t2 1.373 0.177 7.748 0.000
cope5_t2 0.205 0.159 1.290 0.197
cope6_t2 1.265 0.227 5.567 0.000
cope7_t2 0.544 0.166 3.280 0.001
cope8_t2 1.001 0.194 5.164 0.000
cope9_t2 1.000 0.179 5.573 0.000
Refusal_t1 =~
rsmj1_t1 1.000
rsmj2_t1 1.152 0.131 8.807 0.000
rsmj3_t1 1.395 0.124 11.284 0.000
rsmj4_t1 1.003 0.056 17.855 0.000
rsmj5_t1 1.310 0.145 9.014 0.000
Refusal_t2 =~
rsmj1_t2 1.000
rsmj2_t2 1.434 0.153 9.355 0.000
rsmj3_t2 1.422 0.138 10.294 0.000
rsmj4_t2 0.992 0.096 10.372 0.000
rsmj5_t2 1.538 0.169 9.096 0.000
Regressions:
Estimate Std.Err z-value P(>|z|)
attmj_t2 ~
attmj_t1 0.414 0.079 5.257 0.000
peermj_t2 ~
peermj_t1 0.418 0.066 6.376 0.000
knomj_t2 ~
knomj_t1 0.172 0.069 2.499 0.012
rsk5_t2 ~
rsk5_t1 0.536 0.055 9.791 0.000
coping_t2 ~
coping_t1 0.760 0.631 1.204 0.228
Refusal_t2 ~
Refusal_t1 0.484 0.080 6.059 0.000
usemj1_t2 ~
usemj1_t1 0.018 0.039 0.472 0.637
coping_t2 0.135 0.091 1.486 0.137
Refusal_t2 -0.116 0.075 -1.542 0.123
knomj_t2 -0.077 0.093 -0.833 0.405
rsk5_t2 -0.108 0.072 -1.506 0.132
peermj_t2 -0.195 0.071 -2.741 0.006
attmj_t2 0.051 0.059 0.853 0.394
rapd -0.258 0.264 -0.975 0.329
coping_t2 ~
rapd -0.017 0.173 -0.097 0.923
Refusal_t2 ~
rapd 0.426 0.142 3.000 0.003
knomj_t2 ~
rapd 0.057 0.153 0.374 0.708
rsk5_t2 ~
rapd 0.069 0.192 0.361 0.718
peermj_t2 ~
rapd 0.231 0.300 0.769 0.442
attmj_t2 ~
rapd -0.336 0.264 -1.272 0.203
Covariances:
Estimate Std.Err z-value P(>|z|)
.rsmj1_t1 ~~
.rsmj4_t1 0.256 0.052 4.953 0.000
.attmj_t2 ~~
.peermj_t2 0.257 0.062 4.150 0.000
.rsmj1_t2 ~~
.rsmj4_t2 0.203 0.045 4.512 0.000
Refusal_t1 ~~
peermj_t1 0.137 0.041 3.376 0.001
attmj_t1 ~~
peermj_t1 0.393 0.064 6.121 0.000
.cope2_t1 ~~
.cope2_t2 0.150 0.071 2.108 0.035
.cope6_t1 -0.240 0.154 -1.557 0.120
.cope5_t2 ~~
.cope7_t2 0.335 0.067 4.977 0.000
.cope2_t1 ~~
.rsk5_t2 0.135 0.039 3.437 0.001
coping_t1 ~~
Refusal_t1 -0.001 0.011 -0.117 0.907
Intercepts:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 2.502 0.063 39.527 0.000
.cope2_t1 2.469 0.065 37.806 0.000
.cope3_t1 2.822 0.062 45.808 0.000
.cope4_t1 2.769 0.067 41.444 0.000
.cope5_t1 1.990 0.059 33.869 0.000
.cope6_t1 2.917 0.063 46.530 0.000
.cope7_t1 2.531 0.062 40.682 0.000
.cope8_t1 2.376 0.066 35.772 0.000
.cope9_t1 2.667 0.062 42.985 0.000
.cope1_t2 2.812 0.174 16.172 0.000
.cope2_t2 2.473 0.081 30.365 0.000
.cope3_t2 2.629 0.266 9.889 0.000
.cope4_t2 2.989 0.238 12.542 0.000
.cope5_t2 2.257 0.075 30.295 0.000
.cope6_t2 2.915 0.223 13.076 0.000
.cope7_t2 2.428 0.109 22.368 0.000
.cope8_t2 2.280 0.179 12.729 0.000
.cope9_t2 2.653 0.176 15.097 0.000
.rsmj1_t1 3.426 0.054 63.634 0.000
.rsmj2_t1 3.056 0.064 47.752 0.000
.rsmj3_t1 3.165 0.060 52.337 0.000
.rsmj4_t1 3.413 0.055 61.856 0.000
.rsmj5_t1 2.977 0.067 44.393 0.000
.rsmj1_t2 3.061 0.153 19.949 0.000
.rsmj2_t2 2.623 0.183 14.328 0.000
.rsmj3_t2 2.683 0.190 14.142 0.000
.rsmj4_t2 3.051 0.156 19.617 0.000
.rsmj5_t2 2.563 0.203 12.626 0.000
.attmj_t2 2.805 0.408 6.870 0.000
.peermj_t2 1.248 0.313 3.991 0.000
.knomj_t2 0.589 0.147 4.004 0.000
.rsk5_t2 1.128 0.223 5.052 0.000
.usemj1_t2 1.057 0.347 3.044 0.002
attmj_t1 4.363 0.054 81.047 0.000
peermj_t1 2.419 0.048 49.901 0.000
Variances:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 1.189 0.065 18.350 0.000
.cope2_t1 1.239 0.120 10.313 0.000
.cope3_t1 0.702 0.198 3.545 0.000
.cope4_t1 1.309 0.076 17.145 0.000
.cope5_t1 1.036 0.074 14.010 0.000
.cope6_t1 0.941 0.182 5.158 0.000
.cope7_t1 1.161 0.076 15.355 0.000
.cope8_t1 1.128 0.122 9.275 0.000
.cope9_t1 1.166 0.059 19.721 0.000
.cope1_t2 0.715 0.073 9.865 0.000
.cope2_t2 1.272 0.061 20.691 0.000
.cope3_t2 0.651 0.079 8.224 0.000
.cope4_t2 0.479 0.064 7.535 0.000
.cope5_t2 1.255 0.060 20.945 0.000
.cope6_t2 0.882 0.083 10.644 0.000
.cope7_t2 1.016 0.063 16.166 0.000
.cope8_t2 0.852 0.076 11.251 0.000
.cope9_t2 0.995 0.080 12.424 0.000
.rsmj1_t1 0.401 0.052 7.727 0.000
.rsmj2_t1 0.608 0.092 6.587 0.000
.rsmj3_t1 0.179 0.042 4.268 0.000
.rsmj4_t1 0.442 0.062 7.075 0.000
.rsmj5_t1 0.543 0.081 6.733 0.000
.rsmj1_t2 0.428 0.057 7.473 0.000
.rsmj2_t2 0.294 0.050 5.891 0.000
.rsmj3_t2 0.216 0.042 5.092 0.000
.rsmj4_t2 0.513 0.067 7.648 0.000
.rsmj5_t2 0.284 0.048 5.974 0.000
.attmj_t2 0.749 0.102 7.375 0.000
.peermj_t2 0.469 0.054 8.605 0.000
.knomj_t2 0.165 0.013 12.513 0.000
.rsk5_t2 0.341 0.040 8.470 0.000
.usemj1_t2 0.354 0.081 4.358 0.000
attmj_t1 0.878 0.105 8.368 0.000
peermj_t1 0.654 0.061 10.687 0.000
coping_t1 0.024 0.035 0.697 0.486
.coping_t2 0.232 0.066 3.536 0.000
Refusal_t1 0.477 0.095 5.034 0.000
.Refusal_t2 0.237 0.056 4.218 0.000mod_indices <- modindices(MJ_Full_fit)
mod_indices_sorted <- mod_indices[order(-mod_indices$mi), ]
print(mod_indices_sorted) lhs op rhs mi epc sepc.lv sepc.all sepc.nox
954 rsk5_t1 ~ attmj_t1 70.805 0.364 0.364 0.441 0.441
947 rsk5_t1 ~ attmj_t2 63.655 0.340 0.340 0.417 0.417
955 rsk5_t1 ~ peermj_t1 56.160 0.376 0.376 0.393 0.393
812 peermj_t2 ~~ peermj_t1 50.567 -0.313 -0.313 -0.565 -0.565
914 attmj_t1 ~ rsk5_t1 49.509 0.414 0.414 0.342 0.442
906 attmj_t1 ~ peermj_t2 45.301 0.445 0.445 0.363 0.363
948 rsk5_t1 ~ peermj_t2 45.135 0.356 0.356 0.351 0.351
811 peermj_t2 ~~ attmj_t1 42.684 0.198 0.198 0.309 0.309
916 attmj_t1 ~ Refusal_t1 41.547 0.528 0.365 0.389 0.389
983 Refusal_t1 ~ peermj_t1 41.464 0.640 0.927 0.749 0.749
982 Refusal_t1 ~ attmj_t1 41.462 0.287 0.415 0.389 0.389
912 attmj_t1 ~ peermj_t1 41.460 1.840 1.840 1.588 1.588
976 Refusal_t1 ~ peermj_t2 37.002 0.346 0.500 0.382 0.382
958 rsk5_t1 ~ Refusal_t1 36.640 0.373 0.258 0.333 0.333
845 peermj_t2 ~ attmj_t1 36.121 0.287 0.287 0.352 0.352
839 peermj_t2 ~ attmj_t2 36.121 0.695 0.695 0.863 0.863
222 Refusal_t2 =~ cope2_t2 35.968 0.679 0.405 0.356 0.356
482 cope9_t1 ~~ cope7_t2 33.902 0.350 0.350 0.322 0.322
910 attmj_t1 ~ Refusal_t2 33.684 0.492 0.293 0.313 0.313
985 Refusal_t1 ~ rsk5_t1 30.214 0.285 0.412 0.319 0.412
428 cope7_t1 ~~ cope6_t2 29.803 -0.336 -0.336 -0.332 -0.332
864 rsk5_t2 ~ peermj_t2 26.901 0.223 0.223 0.237 0.237
863 rsk5_t2 ~ attmj_t2 26.271 0.177 0.177 0.234 0.234
763 rsmj1_t2 ~~ peermj_t2 25.386 0.107 0.107 0.239 0.239
199 Refusal_t1 =~ cope2_t2 24.983 0.489 0.338 0.298 0.298
271 cope2_t1 ~~ cope5_t1 24.314 0.306 0.306 0.270 0.270
952 rsk5_t1 ~ Refusal_t2 24.082 0.347 0.207 0.267 0.267
975 Refusal_t1 ~ attmj_t2 24.056 0.208 0.302 0.287 0.287
908 attmj_t1 ~ rsk5_t2 23.928 0.310 0.310 0.238 0.238
825 coping_t2 ~~ Refusal_t2 22.811 0.082 0.349 0.349 0.349
363 cope5_t1 ~~ cope7_t1 22.564 0.302 0.302 0.275 0.275
880 coping_t2 ~ usemj1_t2 22.560 -0.718 -1.447 -0.912 -0.912
429 cope7_t1 ~~ cope7_t2 22.192 0.283 0.283 0.261 0.261
529 cope2_t2 ~~ cope5_t2 21.722 0.321 0.321 0.254 0.254
891 Refusal_t2 ~ coping_t2 21.517 0.326 0.272 0.272 0.272
237 cope1_t1 ~~ cope4_t1 21.471 0.340 0.340 0.273 0.273
978 Refusal_t1 ~ rsk5_t2 20.759 0.255 0.369 0.265 0.265
272 cope2_t1 ~~ cope7_t1 20.338 0.296 0.296 0.247 0.247
829 attmj_t2 ~ rsk5_t2 20.082 0.282 0.282 0.213 0.213
771 rsmj2_t2 ~~ rsmj5_t2 20.022 0.143 0.143 0.496 0.496
887 Refusal_t2 ~ attmj_t2 19.834 0.144 0.241 0.229 0.229
920 peermj_t1 ~ peermj_t2 19.377 -0.377 -0.377 -0.356 -0.356
584 cope4_t2 ~~ rsmj1_t2 19.308 0.119 0.119 0.262 0.262
841 peermj_t2 ~ rsk5_t2 18.240 0.213 0.213 0.200 0.200
917 attmj_t1 ~ usemj1_t1 18.094 -0.208 -0.208 -0.207 -0.222
888 Refusal_t2 ~ peermj_t2 18.060 0.172 0.288 0.220 0.220
769 rsmj2_t2 ~~ rsmj3_t2 17.117 -0.123 -0.123 -0.488 -0.488
577 cope4_t2 ~~ cope8_t2 16.622 -0.200 -0.200 -0.314 -0.314
224 Refusal_t2 =~ cope4_t2 16.569 0.323 0.193 0.198 0.198
371 cope5_t1 ~~ cope6_t2 16.459 -0.236 -0.236 -0.247 -0.247
879 coping_t2 ~ Refusal_t2 16.417 0.232 0.279 0.279 0.279
843 peermj_t2 ~ Refusal_t2 15.497 0.251 0.149 0.195 0.195
158 coping_t1 =~ cope8_t2 14.990 1.975 0.307 0.293 0.293
707 rsmj2_t1 ~~ rsmj5_t1 14.638 0.160 0.160 0.279 0.279
832 attmj_t2 ~ usemj1_t2 13.932 -0.618 -0.618 -0.409 -0.409
431 cope7_t1 ~~ cope9_t2 13.779 0.237 0.237 0.220 0.220
738 rsmj4_t1 ~~ rsmj4_t2 13.568 0.073 0.073 0.154 0.154
228 Refusal_t2 =~ cope8_t2 13.273 -0.352 -0.210 -0.200 -0.200
618 cope6_t2 ~~ cope9_t2 13.257 -0.224 -0.224 -0.239 -0.239
835 attmj_t2 ~ rsk5_t1 13.177 0.215 0.215 0.175 0.226
421 cope7_t1 ~~ cope8_t1 12.223 0.252 0.252 0.220 0.220
637 cope7_t2 ~~ cope9_t2 12.156 0.202 0.202 0.201 0.201
981 Refusal_t1 ~ usemj1_t2 12.141 -0.273 -0.395 -0.249 -0.249
692 rsmj1_t1 ~~ rsmj5_t1 12.127 -0.085 -0.085 -0.183 -0.183
427 cope7_t1 ~~ cope5_t2 12.074 -0.231 -0.231 -0.191 -0.191
154 coping_t1 =~ cope4_t2 11.886 -1.504 -0.234 -0.241 -0.241
503 cope1_t2 ~~ cope3_t2 11.453 -0.179 -0.179 -0.263 -0.263
766 rsmj1_t2 ~~ usemj1_t2 11.367 -0.069 -0.069 -0.178 -0.178
490 cope9_t1 ~~ rsmj1_t2 11.209 -0.125 -0.125 -0.176 -0.176
504 cope1_t2 ~~ cope4_t2 10.998 0.153 0.153 0.262 0.262
493 cope9_t1 ~~ rsmj4_t2 10.984 0.134 0.134 0.173 0.173
853 knomj_t2 ~ rsk5_t2 10.944 0.109 0.109 0.189 0.189
779 rsmj3_t2 ~~ rsmj4_t2 10.772 0.073 0.073 0.219 0.219
674 cope9_t2 ~~ rsmj2_t1 10.758 -0.159 -0.159 -0.204 -0.204
890 Refusal_t2 ~ rsk5_t2 10.725 0.141 0.237 0.170 0.170
804 attmj_t2 ~~ rsk5_t2 10.249 0.082 0.082 0.162 0.162
204 Refusal_t1 =~ cope7_t2 10.201 0.271 0.187 0.179 0.179
398 cope6_t1 ~~ cope4_t2 10.072 -0.144 -0.144 -0.215 -0.215
759 rsmj1_t2 ~~ rsmj2_t2 9.955 0.071 0.071 0.199 0.199
809 peermj_t2 ~~ rsk5_t2 9.925 0.064 0.064 0.159 0.159
246 cope1_t1 ~~ cope4_t2 9.900 0.156 0.156 0.206 0.206
322 cope3_t1 ~~ rsmj4_t2 9.854 -0.117 -0.117 -0.195 -0.195
813 knomj_t2 ~~ rsk5_t2 9.693 0.041 0.041 0.175 0.175
251 cope1_t1 ~~ cope9_t2 9.651 -0.201 -0.201 -0.185 -0.185
865 rsk5_t2 ~ knomj_t2 9.510 0.246 0.246 0.141 0.141
651 cope7_t2 ~~ rsk5_t2 9.482 0.098 0.098 0.166 0.166
444 cope7_t1 ~~ knomj_t2 9.435 -0.077 -0.077 -0.177 -0.177
366 cope5_t1 ~~ cope1_t2 9.421 0.159 0.159 0.184 0.184
893 Refusal_t2 ~ attmj_t1 9.402 0.100 0.168 0.158 0.158
1000 usemj1_t1 ~ coping_t1 9.338 1.295 0.202 0.216 0.216
607 cope5_t2 ~~ rsmj4_t2 9.307 -0.122 -0.122 -0.152 -0.152
736 rsmj4_t1 ~~ rsmj2_t2 9.289 -0.057 -0.057 -0.159 -0.159
802 rsmj5_t2 ~~ peermj_t1 9.104 -0.072 -0.072 -0.166 -0.166
282 cope2_t1 ~~ cope9_t2 8.986 0.186 0.186 0.168 0.168
827 attmj_t2 ~ peermj_t2 8.937 0.502 0.502 0.403 0.403
833 attmj_t2 ~ peermj_t1 8.937 0.210 0.210 0.178 0.178
284 cope2_t1 ~~ rsmj2_t1 8.886 -0.148 -0.148 -0.171 -0.171
867 rsk5_t2 ~ Refusal_t2 8.776 0.172 0.103 0.143 0.143
287 cope2_t1 ~~ rsmj5_t1 8.678 -0.142 -0.142 -0.173 -0.173
761 rsmj1_t2 ~~ rsmj5_t2 8.600 -0.067 -0.067 -0.193 -0.193
842 peermj_t2 ~ coping_t2 8.520 0.238 0.118 0.154 0.154
878 coping_t2 ~ rsk5_t2 8.429 0.131 0.265 0.190 0.190
614 cope5_t2 ~~ attmj_t1 8.402 0.141 0.141 0.135 0.135
486 cope9_t1 ~~ rsmj2_t1 8.243 -0.146 -0.146 -0.174 -0.174
849 peermj_t2 ~ Refusal_t1 8.193 0.160 0.110 0.144 0.144
473 cope8_t1 ~~ usemj1_t2 8.124 0.108 0.108 0.171 0.171
168 coping_t1 =~ rsmj4_t2 8.050 -0.921 -0.143 -0.155 -0.155
932 peermj_t1 ~ rapd 8.038 0.579 0.579 0.134 0.716
344 cope4_t1 ~~ cope9_t2 7.865 -0.191 -0.191 -0.167 -0.167
514 cope1_t2 ~~ rsmj5_t1 7.686 -0.112 -0.112 -0.179 -0.179
973 coping_t1 ~ usemj1_t1 7.625 0.036 0.230 0.214 0.230
545 cope2_t2 ~~ peermj_t2 7.525 0.109 0.109 0.141 0.141
549 cope2_t2 ~~ attmj_t1 7.401 0.139 0.139 0.131 0.131
876 coping_t2 ~ peermj_t2 7.384 0.114 0.231 0.176 0.176
572 cope3_t2 ~~ attmj_t1 7.365 -0.112 -0.112 -0.148 -0.148
896 Refusal_t2 ~ rsk5_t1 7.353 0.110 0.184 0.143 0.184
877 coping_t2 ~ knomj_t2 7.247 0.210 0.424 0.175 0.175
725 rsmj3_t1 ~~ rsmj4_t2 7.245 -0.060 -0.060 -0.197 -0.197
700 rsmj1_t1 ~~ knomj_t2 7.195 0.032 0.032 0.124 0.124
704 rsmj1_t1 ~~ peermj_t1 7.188 0.052 0.052 0.102 0.102
993 usemj1_t1 ~ coping_t2 7.178 0.301 0.149 0.160 0.160
320 cope3_t1 ~~ rsmj2_t2 7.062 0.093 0.093 0.205 0.205
227 Refusal_t2 =~ cope7_t2 7.053 0.260 0.155 0.149 0.149
765 rsmj1_t2 ~~ rsk5_t2 7.047 0.052 0.052 0.137 0.137
664 cope8_t2 ~~ rsmj4_t2 6.979 -0.094 -0.094 -0.143 -0.143
807 attmj_t2 ~~ peermj_t1 6.936 0.084 0.084 0.120 0.120
806 attmj_t2 ~~ attmj_t1 6.936 -0.188 -0.188 -0.232 -0.232
312 cope3_t1 ~~ cope8_t2 6.929 0.144 0.144 0.187 0.187
654 cope7_t2 ~~ peermj_t1 6.929 0.097 0.097 0.120 0.120
166 coping_t1 =~ rsmj2_t2 6.920 0.804 0.125 0.124 0.124
454 cope8_t1 ~~ cope5_t2 6.797 -0.178 -0.178 -0.149 -0.149
854 knomj_t2 ~ coping_t2 6.755 0.140 0.069 0.168 0.168
693 rsmj1_t1 ~~ rsmj1_t2 6.739 0.046 0.046 0.110 0.110
705 rsmj2_t1 ~~ rsmj3_t1 6.719 -0.102 -0.102 -0.310 -0.310
270 cope2_t1 ~~ cope4_t1 6.707 0.183 0.183 0.144 0.144
337 cope4_t1 ~~ cope2_t2 6.700 -0.192 -0.192 -0.149 -0.149
847 peermj_t2 ~ rsk5_t1 6.638 0.121 0.121 0.122 0.158
184 coping_t2 =~ rsmj1_t2 6.605 0.204 0.101 0.114 0.114
636 cope7_t2 ~~ cope8_t2 6.448 0.137 0.137 0.148 0.148
770 rsmj2_t2 ~~ rsmj4_t2 6.397 -0.061 -0.061 -0.157 -0.157
403 cope6_t1 ~~ cope9_t2 6.379 0.149 0.149 0.154 0.154
384 cope5_t1 ~~ rsmj5_t2 6.339 -0.092 -0.092 -0.169 -0.169
315 cope3_t1 ~~ rsmj2_t1 6.241 -0.117 -0.117 -0.179 -0.179
531 cope2_t2 ~~ cope7_t2 6.180 0.156 0.156 0.137 0.137
676 cope9_t2 ~~ rsmj4_t1 6.163 0.078 0.078 0.118 0.118
451 cope8_t1 ~~ cope2_t2 6.149 -0.177 -0.177 -0.148 -0.148
538 cope2_t2 ~~ rsmj5_t1 6.085 0.126 0.126 0.152 0.152
1011 rapd ~ peermj_t1 6.001 0.030 0.030 0.132 0.132
747 rsmj5_t1 ~~ rsmj1_t2 5.960 -0.067 -0.067 -0.139 -0.139
298 cope2_t1 ~~ peermj_t1 5.937 0.098 0.098 0.109 0.109
441 cope7_t1 ~~ rsmj5_t2 5.919 -0.094 -0.094 -0.163 -0.163
928 peermj_t1 ~ rsk5_t1 5.858 0.119 0.119 0.114 0.148
474 cope8_t1 ~~ attmj_t1 5.730 -0.121 -0.121 -0.122 -0.122
850 peermj_t2 ~ usemj1_t1 5.727 -0.093 -0.093 -0.113 -0.122
481 cope9_t1 ~~ cope6_t2 5.678 -0.147 -0.147 -0.145 -0.145
443 cope7_t1 ~~ peermj_t2 5.646 0.091 0.091 0.123 0.123
831 attmj_t2 ~ Refusal_t2 5.628 0.189 0.113 0.119 0.119
898 Refusal_t2 ~ usemj1_t1 5.610 -0.080 -0.134 -0.124 -0.134
418 cope6_t1 ~~ usemj1_t2 5.594 0.081 0.081 0.140 0.140
505 cope1_t2 ~~ cope5_t2 5.511 0.129 0.129 0.136 0.136
758 rsmj5_t1 ~~ peermj_t1 5.492 -0.072 -0.072 -0.121 -0.121
364 cope5_t1 ~~ cope8_t1 5.479 0.159 0.159 0.147 0.147
328 cope3_t1 ~~ usemj1_t2 5.475 -0.080 -0.080 -0.160 -0.160
161 coping_t1 =~ rsmj2_t1 5.453 -0.961 -0.150 -0.134 -0.134
695 rsmj1_t1 ~~ rsmj3_t2 5.328 -0.037 -0.037 -0.127 -0.127
742 rsmj4_t1 ~~ knomj_t2 5.302 -0.029 -0.029 -0.106 -0.106
254 cope1_t1 ~~ rsmj3_t1 5.300 -0.086 -0.086 -0.186 -0.186
336 cope4_t1 ~~ cope1_t2 5.230 0.134 0.134 0.138 0.138
522 cope1_t2 ~~ knomj_t2 5.218 0.047 0.047 0.137 0.137
646 cope7_t2 ~~ rsmj4_t2 5.145 0.082 0.082 0.114 0.114
200 Refusal_t1 =~ cope3_t2 5.123 -0.180 -0.124 -0.111 -0.111
711 rsmj2_t1 ~~ rsmj4_t2 5.111 0.070 0.070 0.124 0.124
922 peermj_t1 ~ rsk5_t2 5.108 0.120 0.120 0.107 0.107
580 cope4_t2 ~~ rsmj2_t1 5.104 0.084 0.084 0.155 0.155
739 rsmj4_t1 ~~ rsmj5_t2 5.086 -0.043 -0.043 -0.121 -0.121
242 cope1_t1 ~~ cope9_t1 5.075 0.154 0.154 0.131 0.131
151 coping_t1 =~ cope1_t2 5.047 1.060 0.165 0.168 0.168
405 cope6_t1 ~~ rsmj2_t1 4.937 -0.105 -0.105 -0.138 -0.138
905 attmj_t1 ~ attmj_t2 4.930 0.186 0.186 0.189 0.189
873 rsk5_t2 ~ Refusal_t1 4.801 0.109 0.075 0.105 0.105
243 cope1_t1 ~~ cope1_t2 4.784 0.121 0.121 0.132 0.132
591 cope4_t2 ~~ knomj_t2 4.749 0.040 0.040 0.142 0.142
494 cope9_t1 ~~ rsmj5_t2 4.727 0.084 0.084 0.145 0.145
590 cope4_t2 ~~ peermj_t2 4.685 0.060 0.060 0.127 0.127
457 cope8_t1 ~~ cope8_t2 4.632 0.131 0.131 0.134 0.134
617 cope6_t2 ~~ cope8_t2 4.619 0.124 0.124 0.143 0.143
365 cope5_t1 ~~ cope9_t1 4.569 0.136 0.136 0.123 0.123
789 rsmj4_t2 ~~ attmj_t2 4.535 0.062 0.062 0.100 0.100
400 cope6_t1 ~~ cope6_t2 4.534 0.122 0.122 0.133 0.133
422 cope7_t1 ~~ cope9_t1 4.526 0.143 0.143 0.123 0.123
638 cope7_t2 ~~ rsmj1_t1 4.517 0.060 0.060 0.095 0.095
368 cope5_t1 ~~ cope3_t2 4.485 -0.113 -0.113 -0.137 -0.137
533 cope2_t2 ~~ cope9_t2 4.481 0.141 0.141 0.126 0.126
868 rsk5_t2 ~ usemj1_t2 4.450 -0.181 -0.181 -0.159 -0.159
463 cope8_t1 ~~ rsmj5_t1 4.394 -0.106 -0.106 -0.136 -0.136
866 rsk5_t2 ~ coping_t2 4.370 0.158 0.078 0.109 0.109
541 cope2_t2 ~~ rsmj3_t2 4.366 0.074 0.074 0.142 0.142
406 cope6_t1 ~~ rsmj3_t1 4.344 0.071 0.071 0.173 0.173
635 cope6_t2 ~~ peermj_t1 4.291 -0.078 -0.078 -0.103 -0.103
717 rsmj2_t1 ~~ usemj1_t2 4.290 -0.058 -0.058 -0.126 -0.126
524 cope1_t2 ~~ usemj1_t2 4.270 0.063 0.063 0.126 0.126
476 cope9_t1 ~~ cope1_t2 4.267 -0.113 -0.113 -0.124 -0.124
219 Refusal_t2 =~ cope8_t1 4.254 -0.234 -0.140 -0.121 -0.121
440 cope7_t1 ~~ rsmj4_t2 4.221 0.083 0.083 0.108 0.108
977 Refusal_t1 ~ knomj_t2 4.205 0.199 0.289 0.119 0.119
844 peermj_t2 ~ usemj1_t2 4.164 -0.257 -0.257 -0.212 -0.212
777 rsmj2_t2 ~~ attmj_t1 4.159 -0.057 -0.057 -0.112 -0.112
795 rsmj4_t2 ~~ peermj_t1 4.132 0.051 0.051 0.087 0.087
616 cope6_t2 ~~ cope7_t2 4.086 -0.115 -0.115 -0.121 -0.121
195 Refusal_t1 =~ cope7_t1 4.086 0.191 0.132 0.122 0.122
209 Refusal_t1 =~ rsmj3_t2 4.042 0.131 0.090 0.093 0.093
300 cope3_t1 ~~ cope5_t1 4.029 0.146 0.146 0.171 0.171
488 cope9_t1 ~~ rsmj4_t1 4.027 0.066 0.066 0.092 0.092
309 cope3_t1 ~~ cope5_t2 4.019 0.122 0.122 0.130 0.130
550 cope2_t2 ~~ peermj_t1 3.980 0.085 0.085 0.094 0.094
187 coping_t2 =~ rsmj4_t2 3.966 -0.171 -0.085 -0.092 -0.092
424 cope7_t1 ~~ cope2_t2 3.943 -0.138 -0.138 -0.114 -0.114
745 rsmj4_t1 ~~ attmj_t1 3.933 0.048 0.048 0.077 0.077
245 cope1_t1 ~~ cope3_t2 3.925 -0.113 -0.113 -0.129 -0.129
592 cope4_t2 ~~ rsk5_t2 3.909 0.051 0.051 0.126 0.126
861 knomj_t2 ~ Refusal_t1 3.895 0.070 0.048 0.117 0.117
657 cope8_t2 ~~ rsmj2_t1 3.873 -0.089 -0.089 -0.123 -0.123
339 cope4_t1 ~~ cope4_t2 3.857 0.102 0.102 0.129 0.129
501 cope9_t1 ~~ peermj_t1 3.838 0.081 0.081 0.093 0.093
413 cope6_t1 ~~ rsmj5_t2 3.779 -0.069 -0.069 -0.134 -0.134
631 cope6_t2 ~~ knomj_t2 3.777 0.045 0.045 0.118 0.118
506 cope1_t2 ~~ cope6_t2 3.761 -0.104 -0.104 -0.131 -0.131
793 rsmj4_t2 ~~ usemj1_t2 3.760 0.043 0.043 0.102 0.102
781 rsmj3_t2 ~~ attmj_t2 3.751 0.048 0.048 0.119 0.119
951 rsk5_t1 ~ coping_t2 3.740 0.180 0.089 0.115 0.115
706 rsmj2_t1 ~~ rsmj4_t1 3.712 -0.050 -0.050 -0.096 -0.096
855 knomj_t2 ~ Refusal_t2 3.699 0.080 0.048 0.115 0.115
547 cope2_t2 ~~ rsk5_t2 3.638 0.072 0.072 0.110 0.110
360 cope4_t1 ~~ attmj_t1 3.621 0.100 0.100 0.093 0.093
527 cope2_t2 ~~ cope3_t2 3.608 -0.116 -0.116 -0.128 -0.128
453 cope8_t1 ~~ cope4_t2 3.597 -0.096 -0.096 -0.130 -0.130
927 peermj_t1 ~ knomj_t1 3.578 0.180 0.180 0.089 0.223
334 cope4_t1 ~~ cope8_t1 3.516 -0.147 -0.147 -0.121 -0.121
911 attmj_t1 ~ usemj1_t2 3.478 -0.146 -0.146 -0.098 -0.098
396 cope6_t1 ~~ cope2_t2 3.440 0.125 0.125 0.114 0.114
801 rsmj5_t2 ~~ attmj_t1 3.405 0.052 0.052 0.104 0.104
620 cope6_t2 ~~ rsmj2_t1 3.376 -0.086 -0.086 -0.117 -0.117
450 cope8_t1 ~~ cope1_t2 3.374 0.103 0.103 0.115 0.115
502 cope1_t2 ~~ cope2_t2 3.370 -0.106 -0.106 -0.111 -0.111
886 coping_t2 ~ usemj1_t1 3.362 0.065 0.130 0.122 0.130
586 cope4_t2 ~~ rsmj3_t2 3.360 0.046 0.046 0.142 0.142
180 coping_t2 =~ rsmj2_t1 3.347 -0.198 -0.098 -0.088 -0.088
381 cope5_t1 ~~ rsmj2_t2 3.344 0.066 0.066 0.119 0.119
566 cope3_t2 ~~ rsmj5_t2 3.330 0.059 0.059 0.137 0.137
856 knomj_t2 ~ usemj1_t2 3.327 -0.206 -0.206 -0.314 -0.314
285 cope2_t1 ~~ rsmj3_t1 3.308 0.065 0.065 0.138 0.138
327 cope3_t1 ~~ rsk5_t2 3.289 -0.060 -0.060 -0.122 -0.122
567 cope3_t2 ~~ attmj_t2 3.237 -0.073 -0.073 -0.105 -0.105
393 cope6_t1 ~~ cope8_t1 3.218 0.159 0.159 0.154 0.154
899 usemj1_t2 ~ attmj_t1 3.213 0.072 0.072 0.107 0.107
247 cope1_t1 ~~ cope5_t2 3.186 -0.120 -0.120 -0.098 -0.098
715 rsmj2_t1 ~~ knomj_t2 3.173 0.034 0.034 0.108 0.108
249 cope1_t1 ~~ cope7_t2 3.172 0.109 0.109 0.099 0.099
713 rsmj2_t1 ~~ attmj_t2 3.161 0.065 0.065 0.097 0.097
375 cope5_t1 ~~ rsmj1_t1 3.143 0.053 0.053 0.082 0.082
432 cope7_t1 ~~ rsmj1_t1 3.065 -0.055 -0.055 -0.081 -0.081
283 cope2_t1 ~~ rsmj1_t1 3.027 0.054 0.054 0.076 0.076
391 cope5_t1 ~~ peermj_t1 3.020 0.068 0.068 0.082 0.082
357 cope4_t1 ~~ knomj_t2 3.002 -0.047 -0.047 -0.100 -0.100
751 rsmj5_t1 ~~ rsmj5_t2 2.998 0.049 0.049 0.125 0.125
694 rsmj1_t1 ~~ rsmj2_t2 2.996 0.031 0.031 0.091 0.091
159 coping_t1 =~ cope9_t2 2.972 -0.943 -0.147 -0.132 -0.132
575 cope4_t2 ~~ cope6_t2 2.959 0.093 0.093 0.143 0.143
201 Refusal_t1 =~ cope4_t2 2.955 0.118 0.082 0.084 0.084
511 cope1_t2 ~~ rsmj2_t1 2.945 0.071 0.071 0.108 0.108
658 cope8_t2 ~~ rsmj3_t1 2.933 0.056 0.056 0.142 0.142
264 cope1_t1 ~~ knomj_t2 2.924 -0.044 -0.044 -0.099 -0.099
189 Refusal_t1 =~ cope1_t1 2.875 -0.163 -0.113 -0.102 -0.102
627 cope6_t2 ~~ rsmj4_t2 2.865 0.063 0.063 0.093 0.093
859 knomj_t2 ~ rsk5_t1 2.834 0.052 0.052 0.098 0.127
601 cope5_t2 ~~ rsmj3_t1 2.832 0.061 0.061 0.129 0.129
682 cope9_t2 ~~ rsmj5_t2 2.829 -0.062 -0.062 -0.116 -0.116
448 cope7_t1 ~~ peermj_t1 2.817 0.069 0.069 0.080 0.080
152 coping_t1 =~ cope2_t2 2.809 -0.999 -0.156 -0.137 -0.137
253 cope1_t1 ~~ rsmj2_t1 2.806 0.087 0.087 0.102 0.102
411 cope6_t1 ~~ rsmj3_t2 2.805 0.053 0.053 0.118 0.118
615 cope5_t2 ~~ peermj_t1 2.782 -0.068 -0.068 -0.075 -0.075
685 cope9_t2 ~~ knomj_t2 2.766 -0.040 -0.040 -0.098 -0.098
630 cope6_t2 ~~ peermj_t2 2.766 0.058 0.058 0.091 0.091
652 cope7_t2 ~~ usemj1_t2 2.759 -0.055 -0.055 -0.092 -0.092
206 Refusal_t1 =~ cope9_t2 2.749 0.149 0.103 0.092 0.092
193 Refusal_t1 =~ cope5_t1 2.709 0.147 0.102 0.099 0.099
196 Refusal_t1 =~ cope8_t1 2.703 -0.165 -0.114 -0.099 -0.099
516 cope1_t2 ~~ rsmj2_t2 2.683 0.051 0.051 0.111 0.111
234 Refusal_t2 =~ rsmj5_t1 2.682 0.172 0.103 0.088 0.088
525 cope1_t2 ~~ attmj_t1 2.674 0.066 0.066 0.083 0.083
688 cope9_t2 ~~ attmj_t1 2.673 0.076 0.076 0.082 0.082
491 cope9_t1 ~~ rsmj2_t2 2.660 -0.062 -0.062 -0.106 -0.106
386 cope5_t1 ~~ peermj_t2 2.650 0.059 0.059 0.084 0.084
696 rsmj1_t1 ~~ rsmj4_t2 2.623 -0.031 -0.031 -0.068 -0.068
203 Refusal_t1 =~ cope6_t2 2.618 -0.140 -0.097 -0.086 -0.086
290 cope2_t1 ~~ rsmj3_t2 2.607 -0.054 -0.054 -0.105 -0.105
307 cope3_t1 ~~ cope3_t2 2.582 0.085 0.085 0.126 0.126
957 rsk5_t1 ~ coping_t1 2.579 0.565 0.088 0.114 0.114
370 cope5_t1 ~~ cope5_t2 2.573 0.101 0.101 0.088 0.088
737 rsmj4_t1 ~~ rsmj3_t2 2.568 0.027 0.027 0.088 0.088
324 cope3_t1 ~~ attmj_t2 2.548 -0.071 -0.071 -0.098 -0.098
872 rsk5_t2 ~ coping_t1 2.547 -0.465 -0.072 -0.101 -0.101
301 cope3_t1 ~~ cope6_t1 2.546 -0.205 -0.205 -0.253 -0.253
244 cope1_t1 ~~ cope2_t2 2.538 -0.112 -0.112 -0.091 -0.091
632 cope6_t2 ~~ rsk5_t2 2.532 -0.052 -0.052 -0.094 -0.094
347 cope4_t1 ~~ rsmj3_t1 2.511 0.062 0.062 0.128 0.128
510 cope1_t2 ~~ rsmj1_t1 2.506 0.041 0.041 0.076 0.076
837 attmj_t2 ~ Refusal_t1 2.492 0.108 0.075 0.079 0.079
1003 rapd ~ attmj_t2 2.458 -0.032 -0.032 -0.161 -0.161
643 cope7_t2 ~~ rsmj1_t2 2.456 -0.052 -0.052 -0.079 -0.079
374 cope5_t1 ~~ cope9_t2 2.446 0.094 0.094 0.093 0.093
468 cope8_t1 ~~ rsmj5_t2 2.430 -0.062 -0.062 -0.109 -0.109
169 coping_t1 =~ rsmj5_t2 2.423 -0.481 -0.075 -0.071 -0.071
420 cope6_t1 ~~ peermj_t1 2.409 0.059 0.059 0.076 0.076
293 cope2_t1 ~~ attmj_t2 2.409 -0.073 -0.073 -0.076 -0.076
727 rsmj3_t1 ~~ attmj_t2 2.367 -0.041 -0.041 -0.111 -0.111
369 cope5_t1 ~~ cope4_t2 2.351 0.071 0.071 0.100 0.100
949 rsk5_t1 ~ knomj_t2 2.291 0.146 0.146 0.078 0.078
870 rsk5_t2 ~ peermj_t1 2.274 0.061 0.061 0.069 0.069
295 cope2_t1 ~~ knomj_t2 2.265 -0.037 -0.037 -0.082 -0.082
576 cope4_t2 ~~ cope7_t2 2.254 -0.070 -0.070 -0.100 -0.100
988 Refusal_t1 ~ rapd 2.254 0.323 0.467 0.087 0.467
310 cope3_t1 ~~ cope6_t2 2.253 -0.086 -0.086 -0.109 -0.109
732 rsmj3_t1 ~~ attmj_t1 2.246 0.041 0.041 0.104 0.104
248 cope1_t1 ~~ cope6_t2 2.246 -0.094 -0.094 -0.091 -0.091
953 rsk5_t1 ~ usemj1_t2 2.242 -0.112 -0.112 -0.091 -0.091
670 cope8_t2 ~~ usemj1_t2 2.223 -0.049 -0.049 -0.090 -0.090
361 cope4_t1 ~~ peermj_t1 2.217 0.066 0.066 0.071 0.071
764 rsmj1_t2 ~~ knomj_t2 2.199 0.021 0.021 0.078 0.078
724 rsmj3_t1 ~~ rsmj3_t2 2.187 0.028 0.028 0.143 0.143
581 cope4_t2 ~~ rsmj3_t1 2.142 -0.039 -0.039 -0.133 -0.133
489 cope9_t1 ~~ rsmj5_t1 2.137 -0.072 -0.072 -0.091 -0.091
359 cope4_t1 ~~ usemj1_t2 2.133 0.058 0.058 0.085 0.085
280 cope2_t1 ~~ cope7_t2 2.131 0.086 0.086 0.076 0.076
348 cope4_t1 ~~ rsmj4_t1 2.112 -0.051 -0.051 -0.067 -0.067
185 coping_t2 =~ rsmj2_t2 2.093 0.117 0.058 0.057 0.057
521 cope1_t2 ~~ peermj_t2 2.085 -0.045 -0.045 -0.078 -0.078
509 cope1_t2 ~~ cope9_t2 2.071 0.078 0.078 0.092 0.092
218 Refusal_t2 =~ cope7_t1 2.069 0.157 0.094 0.086 0.086
741 rsmj4_t1 ~~ peermj_t2 2.066 0.027 0.027 0.060 0.060
477 cope9_t1 ~~ cope2_t2 2.050 -0.100 -0.100 -0.082 -0.082
434 cope7_t1 ~~ rsmj3_t1 2.021 0.052 0.052 0.114 0.114
464 cope8_t1 ~~ rsmj1_t2 2.016 -0.054 -0.054 -0.078 -0.078
900 usemj1_t2 ~ peermj_t1 2.011 0.068 0.068 0.087 0.087
162 coping_t1 =~ rsmj3_t1 1.981 0.439 0.068 0.065 0.065
639 cope7_t2 ~~ rsmj2_t1 1.966 -0.064 -0.064 -0.082 -0.082
178 coping_t2 =~ cope9_t1 1.958 -0.211 -0.105 -0.097 -0.097
883 coping_t2 ~ knomj_t1 1.946 0.116 0.233 0.093 0.233
308 cope3_t1 ~~ cope4_t2 1.930 -0.064 -0.064 -0.110 -0.110
720 rsmj3_t1 ~~ rsmj4_t1 1.929 0.031 0.031 0.109 0.109
528 cope2_t2 ~~ cope4_t2 1.923 0.074 0.074 0.094 0.094
480 cope9_t1 ~~ cope5_t2 1.914 -0.092 -0.092 -0.076 -0.076
594 cope4_t2 ~~ attmj_t1 1.898 0.049 0.049 0.076 0.076
279 cope2_t1 ~~ cope6_t2 1.877 -0.082 -0.082 -0.079 -0.079
435 cope7_t1 ~~ rsmj4_t1 1.867 0.045 0.045 0.063 0.063
379 cope5_t1 ~~ rsmj5_t1 1.863 -0.064 -0.064 -0.085 -0.085
555 cope3_t2 ~~ cope8_t2 1.848 0.077 0.077 0.103 0.103
667 cope8_t2 ~~ peermj_t2 1.828 0.046 0.046 0.072 0.072
205 Refusal_t1 =~ cope8_t2 1.813 -0.112 -0.078 -0.074 -0.074
980 Refusal_t1 ~ Refusal_t2 1.803 0.347 0.299 0.299 0.299
288 cope2_t1 ~~ rsmj1_t2 1.766 0.048 0.048 0.066 0.066
392 cope6_t1 ~~ cope7_t1 1.763 -0.087 -0.087 -0.084 -0.084
593 cope4_t2 ~~ usemj1_t2 1.762 -0.037 -0.037 -0.091 -0.091
438 cope7_t1 ~~ rsmj2_t2 1.756 0.050 0.050 0.086 0.086
649 cope7_t2 ~~ peermj_t2 1.734 -0.045 -0.045 -0.066 -0.066
805 attmj_t2 ~~ usemj1_t2 1.723 -0.090 -0.090 -0.174 -0.174
589 cope4_t2 ~~ attmj_t2 1.715 0.046 0.046 0.077 0.077
192 Refusal_t1 =~ cope4_t1 1.705 0.132 0.091 0.079 0.079
648 cope7_t2 ~~ attmj_t2 1.698 0.057 0.057 0.065 0.065
544 cope2_t2 ~~ attmj_t2 1.693 0.065 0.065 0.067 0.067
624 cope6_t2 ~~ rsmj1_t2 1.688 -0.044 -0.044 -0.072 -0.072
996 usemj1_t1 ~ attmj_t1 1.674 -0.067 -0.067 -0.068 -0.068
564 cope3_t2 ~~ rsmj3_t2 1.664 -0.037 -0.037 -0.099 -0.099
215 Refusal_t2 =~ cope4_t1 1.660 0.150 0.090 0.077 0.077
216 Refusal_t2 =~ cope5_t1 1.651 0.132 0.079 0.077 0.077
875 coping_t2 ~ attmj_t2 1.617 0.043 0.087 0.083 0.083
211 Refusal_t1 =~ rsmj5_t2 1.615 -0.092 -0.063 -0.060 -0.060
712 rsmj2_t1 ~~ rsmj5_t2 1.599 -0.037 -0.037 -0.089 -0.089
587 cope4_t2 ~~ rsmj4_t2 1.599 -0.037 -0.037 -0.075 -0.075
786 rsmj3_t2 ~~ attmj_t1 1.594 0.032 0.032 0.073 0.073
987 Refusal_t1 ~ usemj1_t1 1.578 -0.054 -0.078 -0.073 -0.078
569 cope3_t2 ~~ knomj_t2 1.560 -0.027 -0.027 -0.081 -0.081
680 cope9_t2 ~~ rsmj3_t2 1.551 0.041 0.041 0.088 0.088
904 usemj1_t2 ~ Refusal_t1 1.536 -0.082 -0.057 -0.090 -0.090
1001 usemj1_t1 ~ Refusal_t1 1.534 0.092 0.064 0.068 0.068
518 cope1_t2 ~~ rsmj4_t2 1.533 0.041 0.041 0.067 0.067
373 cope5_t1 ~~ cope8_t2 1.523 0.069 0.069 0.074 0.074
208 Refusal_t1 =~ rsmj2_t2 1.518 -0.087 -0.060 -0.059 -0.059
974 coping_t1 ~ rapd 1.494 -0.080 -0.511 -0.096 -0.511
909 attmj_t1 ~ coping_t2 1.491 0.128 0.063 0.068 0.068
965 coping_t1 ~ coping_t2 1.486 2.037 6.490 6.490 6.490
967 coping_t1 ~ usemj1_t2 1.480 0.025 0.159 0.100 0.100
869 rsk5_t2 ~ attmj_t1 1.480 0.043 0.043 0.056 0.056
278 cope2_t1 ~~ cope5_t2 1.469 -0.079 -0.079 -0.063 -0.063
252 cope1_t1 ~~ rsmj1_t1 1.453 -0.039 -0.039 -0.056 -0.056
574 cope4_t2 ~~ cope5_t2 1.449 -0.061 -0.061 -0.079 -0.079
1005 rapd ~ knomj_t2 1.441 -0.111 -0.111 -0.245 -0.245
625 cope6_t2 ~~ rsmj2_t2 1.441 -0.042 -0.042 -0.082 -0.082
269 cope2_t1 ~~ cope3_t1 1.435 -0.108 -0.108 -0.115 -0.115
229 Refusal_t2 =~ cope9_t2 1.433 0.124 0.074 0.066 0.066
517 cope1_t2 ~~ rsmj3_t2 1.429 -0.034 -0.034 -0.085 -0.085
341 cope4_t1 ~~ cope6_t2 1.428 -0.079 -0.079 -0.073 -0.073
526 cope1_t2 ~~ peermj_t1 1.417 0.040 0.040 0.059 0.059
852 knomj_t2 ~ peermj_t2 1.415 0.036 0.036 0.067 0.067
794 rsmj4_t2 ~~ attmj_t1 1.406 0.035 0.035 0.052 0.052
321 cope3_t1 ~~ rsmj3_t2 1.391 -0.037 -0.037 -0.096 -0.096
718 rsmj2_t1 ~~ attmj_t1 1.388 -0.044 -0.044 -0.060 -0.060
387 cope5_t1 ~~ knomj_t2 1.383 -0.028 -0.028 -0.068 -0.068
520 cope1_t2 ~~ attmj_t2 1.376 0.046 0.046 0.063 0.063
943 knomj_t1 ~ coping_t1 1.368 -0.222 -0.035 -0.086 -0.086
708 rsmj2_t1 ~~ rsmj1_t2 1.366 -0.033 -0.033 -0.065 -0.065
233 Refusal_t2 =~ rsmj4_t1 1.358 -0.080 -0.048 -0.050 -0.050
570 cope3_t2 ~~ rsk5_t2 1.356 0.035 0.035 0.074 0.074
221 Refusal_t2 =~ cope1_t2 1.351 0.104 0.062 0.063 0.063
423 cope7_t1 ~~ cope1_t2 1.350 -0.064 -0.064 -0.070 -0.070
383 cope5_t1 ~~ rsmj4_t2 1.332 0.044 0.044 0.060 0.060
666 cope8_t2 ~~ attmj_t2 1.328 -0.049 -0.049 -0.062 -0.062
884 coping_t2 ~ rsk5_t1 1.319 0.049 0.098 0.076 0.098
460 cope8_t1 ~~ rsmj2_t1 1.313 0.060 0.060 0.072 0.072
703 rsmj1_t1 ~~ attmj_t1 1.311 -0.027 -0.027 -0.045 -0.045
495 cope9_t1 ~~ attmj_t2 1.309 -0.055 -0.055 -0.059 -0.059
723 rsmj3_t1 ~~ rsmj2_t2 1.308 -0.024 -0.024 -0.105 -0.105
650 cope7_t2 ~~ knomj_t2 1.302 0.026 0.026 0.063 0.063
628 cope6_t2 ~~ rsmj5_t2 1.292 0.040 0.040 0.080 0.080
858 knomj_t2 ~ peermj_t1 1.288 0.033 0.033 0.064 0.064
774 rsmj2_t2 ~~ knomj_t2 1.286 0.016 0.016 0.074 0.074
458 cope8_t1 ~~ cope9_t2 1.286 -0.074 -0.074 -0.070 -0.070
255 cope1_t1 ~~ rsmj4_t1 1.278 0.038 0.038 0.052 0.052
1015 rapd ~ Refusal_t1 1.263 0.017 0.012 0.064 0.064
773 rsmj2_t2 ~~ peermj_t2 1.262 -0.024 -0.024 -0.066 -0.066
395 cope6_t1 ~~ cope1_t2 1.251 -0.057 -0.057 -0.069 -0.069
553 cope3_t2 ~~ cope6_t2 1.245 0.069 0.069 0.091 0.091
851 knomj_t2 ~ attmj_t2 1.242 0.027 0.027 0.063 0.063
523 cope1_t2 ~~ rsk5_t2 1.240 -0.032 -0.032 -0.065 -0.065
325 cope3_t1 ~~ peermj_t2 1.232 0.039 0.039 0.068 0.068
964 coping_t1 ~ rsk5_t2 1.228 -0.019 -0.120 -0.086 -0.086
690 rsmj1_t1 ~~ rsmj2_t1 1.224 0.027 0.027 0.056 0.056
894 Refusal_t2 ~ peermj_t1 1.207 0.043 0.072 0.059 0.059
681 cope9_t2 ~~ rsmj4_t2 1.202 -0.042 -0.042 -0.059 -0.059
995 usemj1_t1 ~ usemj1_t2 1.201 0.190 0.190 0.128 0.128
498 cope9_t1 ~~ rsk5_t2 1.187 0.039 0.039 0.061 0.061
446 cope7_t1 ~~ usemj1_t2 1.186 0.040 0.040 0.063 0.063
619 cope6_t2 ~~ rsmj1_t1 1.174 -0.031 -0.031 -0.053 -0.053
860 knomj_t2 ~ coping_t1 1.158 0.218 0.034 0.082 0.082
552 cope3_t2 ~~ cope5_t2 1.152 -0.063 -0.063 -0.069 -0.069
768 rsmj1_t2 ~~ peermj_t1 1.151 0.025 0.025 0.046 0.046
778 rsmj2_t2 ~~ peermj_t1 1.143 0.025 0.025 0.057 0.057
903 usemj1_t2 ~ coping_t1 1.140 0.336 0.052 0.083 0.083
585 cope4_t2 ~~ rsmj2_t2 1.133 -0.029 -0.029 -0.079 -0.079
857 knomj_t2 ~ attmj_t1 1.129 0.026 0.026 0.060 0.060
796 rsmj5_t2 ~~ attmj_t2 1.128 -0.030 -0.030 -0.064 -0.064
240 cope1_t1 ~~ cope7_t1 1.122 0.072 0.072 0.062 0.062
447 cope7_t1 ~~ attmj_t1 1.114 -0.052 -0.052 -0.051 -0.051
188 coping_t2 =~ rsmj5_t2 1.111 0.086 0.043 0.040 0.040
984 Refusal_t1 ~ knomj_t1 1.107 0.105 0.152 0.061 0.152
889 Refusal_t2 ~ knomj_t2 1.103 0.078 0.131 0.054 0.054
539 cope2_t2 ~~ rsmj1_t2 1.099 0.040 0.040 0.055 0.055
820 usemj1_t2 ~~ attmj_t1 1.094 0.031 0.031 0.055 0.055
881 coping_t2 ~ attmj_t1 1.091 0.036 0.072 0.068 0.068
728 rsmj3_t1 ~~ peermj_t2 1.090 0.022 0.022 0.075 0.075
612 cope5_t2 ~~ rsk5_t2 1.078 -0.036 -0.036 -0.056 -0.056
465 cope8_t1 ~~ rsmj2_t2 1.071 0.040 0.040 0.070 0.070
232 Refusal_t2 =~ rsmj3_t1 1.069 -0.090 -0.054 -0.051 -0.051
202 Refusal_t1 =~ cope5_t2 1.065 0.096 0.067 0.059 0.059
225 Refusal_t2 =~ cope5_t2 1.059 0.111 0.066 0.059 0.059
410 cope6_t1 ~~ rsmj2_t2 1.057 -0.036 -0.036 -0.069 -0.069
306 cope3_t1 ~~ cope2_t2 1.057 -0.066 -0.066 -0.070 -0.070
668 cope8_t2 ~~ knomj_t2 1.052 -0.023 -0.023 -0.061 -0.061
507 cope1_t2 ~~ cope7_t2 1.038 -0.051 -0.051 -0.060 -0.060
709 rsmj2_t1 ~~ rsmj2_t2 1.032 0.029 0.029 0.070 0.070
702 rsmj1_t1 ~~ usemj1_t2 1.018 0.018 0.018 0.047 0.047
362 cope5_t1 ~~ cope6_t1 1.009 -0.062 -0.062 -0.063 -0.063
536 cope2_t2 ~~ rsmj3_t1 1.001 -0.038 -0.038 -0.080 -0.080
535 cope2_t2 ~~ rsmj2_t1 0.986 0.053 0.053 0.060 0.060
687 cope9_t2 ~~ usemj1_t2 0.984 0.035 0.035 0.059 0.059
157 coping_t1 =~ cope7_t2 0.967 -0.504 -0.078 -0.075 -0.075
918 attmj_t1 ~ rapd 0.962 0.239 0.239 0.048 0.255
697 rsmj1_t1 ~~ rsmj5_t2 0.949 0.018 0.018 0.053 0.053
749 rsmj5_t1 ~~ rsmj3_t2 0.949 0.025 0.025 0.072 0.072
672 cope8_t2 ~~ peermj_t1 0.943 -0.035 -0.035 -0.048 -0.048
340 cope4_t1 ~~ cope5_t2 0.942 -0.069 -0.069 -0.054 -0.054
230 Refusal_t2 =~ rsmj1_t1 0.934 0.063 0.038 0.040 0.040
923 peermj_t1 ~ coping_t2 0.914 -0.084 -0.042 -0.052 -0.052
194 Refusal_t1 =~ cope6_t1 0.909 0.087 0.060 0.055 0.055
167 coping_t1 =~ rsmj3_t2 0.908 0.263 0.041 0.042 0.042
729 rsmj3_t1 ~~ knomj_t2 0.907 -0.013 -0.013 -0.076 -0.076
394 cope6_t1 ~~ cope9_t1 0.898 -0.062 -0.062 -0.059 -0.059
289 cope2_t1 ~~ rsmj2_t2 0.896 0.035 0.035 0.058 0.058
686 cope9_t2 ~~ rsk5_t2 0.889 0.032 0.032 0.054 0.054
155 coping_t1 =~ cope5_t2 0.881 0.529 0.082 0.073 0.073
655 cope8_t2 ~~ cope9_t2 0.878 -0.055 -0.055 -0.059 -0.059
834 attmj_t2 ~ knomj_t1 0.870 0.108 0.108 0.045 0.113
757 rsmj5_t1 ~~ attmj_t1 0.867 0.034 0.034 0.049 0.049
744 rsmj4_t1 ~~ usemj1_t2 0.862 -0.017 -0.017 -0.043 -0.043
970 coping_t1 ~ knomj_t1 0.856 -0.028 -0.179 -0.072 -0.179
719 rsmj2_t1 ~~ peermj_t1 0.852 -0.029 -0.029 -0.046 -0.046
663 cope8_t2 ~~ rsmj3_t2 0.849 -0.028 -0.028 -0.065 -0.065
367 cope5_t1 ~~ cope2_t2 0.840 0.060 0.060 0.052 0.052
197 Refusal_t1 =~ cope9_t1 0.827 -0.086 -0.059 -0.055 -0.055
691 rsmj1_t1 ~~ rsmj3_t1 0.826 0.019 0.019 0.073 0.073
644 cope7_t2 ~~ rsmj2_t2 0.824 0.031 0.031 0.057 0.057
250 cope1_t1 ~~ cope8_t2 0.817 0.054 0.054 0.054 0.054
963 coping_t1 ~ knomj_t2 0.815 0.026 0.170 0.070 0.070
1006 rapd ~ rsk5_t2 0.812 0.030 0.030 0.117 0.117
925 peermj_t1 ~ usemj1_t2 0.788 0.060 0.060 0.047 0.047
662 cope8_t2 ~~ rsmj2_t2 0.772 0.030 0.030 0.059 0.059
297 cope2_t1 ~~ attmj_t1 0.765 0.042 0.042 0.040 0.040
782 rsmj3_t2 ~~ peermj_t2 0.756 0.017 0.017 0.054 0.054
378 cope5_t1 ~~ rsmj4_t1 0.756 -0.027 -0.027 -0.040 -0.040
559 cope3_t2 ~~ rsmj3_t1 0.755 -0.027 -0.027 -0.078 -0.078
175 coping_t2 =~ cope6_t1 0.753 -0.133 -0.066 -0.060 -0.060
683 cope9_t2 ~~ attmj_t2 0.743 -0.040 -0.040 -0.046 -0.046
935 knomj_t1 ~ knomj_t2 0.740 -0.240 -0.240 -0.247 -0.247
821 usemj1_t2 ~~ peermj_t1 0.733 0.021 0.021 0.044 0.044
415 cope6_t1 ~~ peermj_t2 0.727 -0.030 -0.030 -0.045 -0.045
238 cope1_t1 ~~ cope5_t1 0.725 -0.055 -0.055 -0.050 -0.050
326 cope3_t1 ~~ knomj_t2 0.722 0.020 0.020 0.058 0.058
788 rsmj4_t2 ~~ rsmj5_t2 0.722 -0.021 -0.021 -0.055 -0.055
294 cope2_t1 ~~ peermj_t2 0.718 0.032 0.032 0.042 0.042
190 Refusal_t1 =~ cope2_t1 0.715 -0.078 -0.054 -0.048 -0.048
775 rsmj2_t2 ~~ rsk5_t2 0.712 0.017 0.017 0.054 0.054
606 cope5_t2 ~~ rsmj3_t2 0.712 0.029 0.029 0.055 0.055
990 usemj1_t1 ~ peermj_t2 0.709 -0.054 -0.054 -0.044 -0.044
281 cope2_t1 ~~ cope8_t2 0.706 -0.049 -0.049 -0.047 -0.047
907 attmj_t1 ~ knomj_t2 0.705 0.093 0.093 0.041 0.041
560 cope3_t2 ~~ rsmj4_t1 0.704 -0.023 -0.023 -0.044 -0.044
565 cope3_t2 ~~ rsmj4_t2 0.678 -0.028 -0.028 -0.048 -0.048
358 cope4_t1 ~~ rsk5_t2 0.676 -0.031 -0.031 -0.047 -0.047
671 cope8_t2 ~~ attmj_t1 0.673 -0.036 -0.036 -0.041 -0.041
621 cope6_t2 ~~ rsmj3_t1 0.672 0.028 0.028 0.069 0.069
815 knomj_t2 ~~ attmj_t1 0.671 0.015 0.015 0.040 0.040
800 rsmj5_t2 ~~ usemj1_t2 0.664 0.018 0.018 0.056 0.056
262 cope1_t1 ~~ attmj_t2 0.657 0.040 0.040 0.042 0.042
599 cope5_t2 ~~ rsmj1_t1 0.656 -0.025 -0.025 -0.036 -0.036
810 peermj_t2 ~~ usemj1_t2 0.641 -0.040 -0.040 -0.098 -0.098
611 cope5_t2 ~~ knomj_t2 0.635 -0.020 -0.020 -0.044 -0.044
750 rsmj5_t1 ~~ rsmj4_t2 0.633 -0.024 -0.024 -0.045 -0.045
734 rsmj4_t1 ~~ rsmj5_t1 0.633 0.020 0.020 0.041 0.041
783 rsmj3_t2 ~~ knomj_t2 0.632 -0.010 -0.010 -0.054 -0.054
176 coping_t2 =~ cope7_t1 0.632 -0.120 -0.060 -0.055 -0.055
512 cope1_t2 ~~ rsmj3_t1 0.630 -0.024 -0.024 -0.066 -0.066
600 cope5_t2 ~~ rsmj2_t1 0.622 -0.040 -0.040 -0.046 -0.046
470 cope8_t1 ~~ peermj_t2 0.620 -0.031 -0.031 -0.043 -0.043
818 rsk5_t2 ~~ attmj_t1 0.619 0.020 0.020 0.037 0.037
467 cope8_t1 ~~ rsmj4_t2 0.614 0.033 0.033 0.043 0.043
934 knomj_t1 ~ peermj_t2 0.609 0.022 0.022 0.043 0.043
597 cope5_t2 ~~ cope8_t2 0.606 -0.046 -0.046 -0.045 -0.045
407 cope6_t1 ~~ rsmj4_t1 0.599 0.024 0.024 0.037 0.037
824 coping_t2 ~~ Refusal_t1 0.596 0.017 0.053 0.053 0.053
633 cope6_t2 ~~ usemj1_t2 0.593 0.027 0.027 0.048 0.048
660 cope8_t2 ~~ rsmj5_t1 0.591 -0.034 -0.034 -0.049 -0.049
822 coping_t1 ~~ coping_t2 0.590 0.330 4.399 4.399 4.399
623 cope6_t2 ~~ rsmj5_t1 0.589 0.035 0.035 0.050 0.050
997 usemj1_t1 ~ peermj_t1 0.586 0.046 0.046 0.040 0.040
595 cope4_t2 ~~ peermj_t1 0.579 -0.023 -0.023 -0.041 -0.041
979 Refusal_t1 ~ coping_t2 0.579 0.074 0.053 0.053 0.053
679 cope9_t2 ~~ rsmj2_t2 0.578 0.028 0.028 0.051 0.051
556 cope3_t2 ~~ cope9_t2 0.576 0.045 0.045 0.056 0.056
445 cope7_t1 ~~ rsk5_t2 0.575 0.027 0.027 0.043 0.043
333 cope4_t1 ~~ cope7_t1 0.572 -0.055 -0.055 -0.044 -0.044
241 cope1_t1 ~~ cope8_t1 0.567 -0.055 -0.055 -0.048 -0.048
462 cope8_t1 ~~ rsmj4_t1 0.561 -0.025 -0.025 -0.036 -0.036
532 cope2_t2 ~~ cope8_t2 0.552 -0.046 -0.046 -0.044 -0.044
790 rsmj4_t2 ~~ peermj_t2 0.549 -0.017 -0.017 -0.035 -0.035
425 cope7_t1 ~~ cope3_t2 0.544 0.042 0.042 0.048 0.048
469 cope8_t1 ~~ attmj_t2 0.543 0.037 0.037 0.040 0.040
171 coping_t2 =~ cope2_t1 0.533 0.109 0.054 0.048 0.048
677 cope9_t2 ~~ rsmj5_t1 0.529 0.034 0.034 0.046 0.046
496 cope9_t1 ~~ peermj_t2 0.527 -0.028 -0.028 -0.038 -0.038
236 cope1_t1 ~~ cope3_t1 0.512 -0.057 -0.057 -0.063 -0.063
172 coping_t2 =~ cope3_t1 0.508 0.133 0.066 0.062 0.062
380 cope5_t1 ~~ rsmj1_t2 0.503 0.025 0.025 0.037 0.037
534 cope2_t2 ~~ rsmj1_t1 0.503 -0.023 -0.023 -0.033 -0.033
675 cope9_t2 ~~ rsmj3_t1 0.494 0.025 0.025 0.058 0.058
263 cope1_t1 ~~ peermj_t2 0.492 -0.027 -0.027 -0.036 -0.036
385 cope5_t1 ~~ attmj_t2 0.486 -0.032 -0.032 -0.036 -0.036
746 rsmj4_t1 ~~ peermj_t1 0.477 0.014 0.014 0.026 0.026
183 coping_t2 =~ rsmj5_t1 0.470 -0.072 -0.036 -0.031 -0.031
762 rsmj1_t2 ~~ attmj_t2 0.469 -0.018 -0.018 -0.032 -0.032
499 cope9_t1 ~~ usemj1_t2 0.465 -0.025 -0.025 -0.039 -0.039
226 Refusal_t2 =~ cope6_t2 0.462 -0.068 -0.041 -0.036 -0.036
915 attmj_t1 ~ coping_t1 0.458 -0.270 -0.042 -0.045 -0.045
919 peermj_t1 ~ attmj_t2 0.457 0.030 0.030 0.035 0.035
826 Refusal_t1 ~~ Refusal_t2 0.446 0.048 0.142 0.142 0.142
335 cope4_t1 ~~ cope9_t1 0.445 0.048 0.048 0.039 0.039
661 cope8_t2 ~~ rsmj1_t2 0.442 -0.022 -0.022 -0.036 -0.036
352 cope4_t1 ~~ rsmj3_t2 0.437 0.024 0.024 0.046 0.046
937 knomj_t1 ~ coping_t2 0.429 0.033 0.016 0.041 0.041
785 rsmj3_t2 ~~ usemj1_t2 0.413 0.012 0.012 0.045 0.045
1007 rapd ~ coping_t2 0.412 -0.037 -0.018 -0.098 -0.098
1010 rapd ~ attmj_t1 0.412 0.007 0.007 0.034 0.034
265 cope1_t1 ~~ rsk5_t2 0.408 -0.023 -0.023 -0.036 -0.036
557 cope3_t2 ~~ rsmj1_t1 0.405 -0.017 -0.017 -0.033 -0.033
484 cope9_t1 ~~ cope9_t2 0.401 0.040 0.040 0.037 0.037
605 cope5_t2 ~~ rsmj2_t2 0.392 0.024 0.024 0.039 0.039
173 coping_t2 =~ cope4_t1 0.384 0.101 0.050 0.043 0.043
760 rsmj1_t2 ~~ rsmj3_t2 0.381 -0.013 -0.013 -0.042 -0.042
258 cope1_t1 ~~ rsmj2_t2 0.376 0.024 0.024 0.040 0.040
449 cope8_t1 ~~ cope9_t1 0.375 0.044 0.044 0.038 0.038
217 Refusal_t2 =~ cope6_t1 0.372 -0.063 -0.037 -0.034 -0.034
862 knomj_t2 ~ usemj1_t1 0.369 -0.016 -0.016 -0.035 -0.038
828 attmj_t2 ~ knomj_t2 0.363 0.066 0.066 0.028 0.028
212 Refusal_t2 =~ cope1_t1 0.359 -0.066 -0.040 -0.036 -0.036
748 rsmj5_t1 ~~ rsmj2_t2 0.356 0.017 0.017 0.042 0.042
402 cope6_t1 ~~ cope8_t2 0.349 -0.032 -0.032 -0.036 -0.036
492 cope9_t1 ~~ rsmj3_t2 0.349 -0.020 -0.020 -0.040 -0.040
500 cope9_t1 ~~ attmj_t1 0.348 -0.029 -0.029 -0.029 -0.029
316 cope3_t1 ~~ rsmj3_t1 0.345 0.020 0.020 0.057 0.057
389 cope5_t1 ~~ usemj1_t2 0.344 -0.020 -0.020 -0.034 -0.034
213 Refusal_t2 =~ cope2_t1 0.343 -0.062 -0.037 -0.033 -0.033
941 knomj_t1 ~ peermj_t1 0.338 0.016 0.016 0.032 0.032
318 cope3_t1 ~~ rsmj5_t1 0.333 0.026 0.026 0.043 0.043
497 cope9_t1 ~~ knomj_t2 0.332 0.015 0.015 0.033 0.033
319 cope3_t1 ~~ rsmj1_t2 0.328 0.020 0.020 0.036 0.036
1014 rapd ~ coping_t1 0.327 -0.050 -0.008 -0.042 -0.042
537 cope2_t2 ~~ rsmj4_t1 0.326 0.020 0.020 0.026 0.026
961 coping_t1 ~ attmj_t2 0.324 -0.007 -0.046 -0.044 -0.044
186 coping_t2 =~ rsmj3_t2 0.322 0.041 0.021 0.021 0.021
797 rsmj5_t2 ~~ peermj_t2 0.320 -0.012 -0.012 -0.034 -0.034
830 attmj_t2 ~ coping_t2 0.318 -0.058 -0.029 -0.030 -0.030
220 Refusal_t2 =~ cope9_t1 0.317 -0.061 -0.037 -0.034 -0.034
968 coping_t1 ~ attmj_t1 0.316 -0.007 -0.047 -0.044 -0.044
722 rsmj3_t1 ~~ rsmj1_t2 0.316 0.011 0.011 0.041 0.041
153 coping_t1 =~ cope3_t2 0.312 0.281 0.044 0.039 0.039
645 cope7_t2 ~~ rsmj3_t2 0.312 -0.017 -0.017 -0.037 -0.037
408 cope6_t1 ~~ rsmj5_t1 0.304 -0.025 -0.025 -0.035 -0.035
836 attmj_t2 ~ coping_t1 0.300 -0.213 -0.033 -0.035 -0.035
684 cope9_t2 ~~ peermj_t2 0.298 0.020 0.020 0.029 0.029
840 peermj_t2 ~ knomj_t2 0.297 0.047 0.047 0.025 0.025
598 cope5_t2 ~~ cope9_t2 0.297 0.035 0.035 0.031 0.031
356 cope4_t1 ~~ peermj_t2 0.295 -0.022 -0.022 -0.028 -0.028
994 usemj1_t1 ~ Refusal_t2 0.291 -0.046 -0.027 -0.029 -0.029
223 Refusal_t2 =~ cope3_t2 0.290 -0.050 -0.030 -0.026 -0.026
921 peermj_t1 ~ knomj_t2 0.288 0.050 0.050 0.025 0.025
563 cope3_t2 ~~ rsmj2_t2 0.284 0.017 0.017 0.039 0.039
461 cope8_t1 ~~ rsmj3_t1 0.279 0.020 0.020 0.044 0.044
714 rsmj2_t1 ~~ peermj_t2 0.279 -0.015 -0.015 -0.029 -0.029
1009 rapd ~ usemj1_t2 0.269 -0.027 -0.027 -0.091 -0.091
198 Refusal_t1 =~ cope1_t2 0.268 0.040 0.028 0.028 0.028
472 cope8_t1 ~~ rsk5_t2 0.268 -0.019 -0.019 -0.030 -0.030
317 cope3_t1 ~~ rsmj4_t1 0.267 0.016 0.016 0.028 0.028
767 rsmj1_t2 ~~ attmj_t1 0.262 0.014 0.014 0.023 0.023
299 cope3_t1 ~~ cope4_t1 0.258 0.044 0.044 0.046 0.046
608 cope5_t2 ~~ rsmj5_t2 0.257 0.019 0.019 0.032 0.032
372 cope5_t1 ~~ cope7_t2 0.257 0.029 0.029 0.028 0.028
376 cope5_t1 ~~ rsmj2_t1 0.256 0.024 0.024 0.031 0.031
261 cope1_t1 ~~ rsmj5_t2 0.251 -0.020 -0.020 -0.034 -0.034
669 cope8_t2 ~~ rsk5_t2 0.248 -0.016 -0.016 -0.029 -0.029
950 rsk5_t1 ~ rsk5_t2 0.248 0.060 0.060 0.055 0.055
808 peermj_t2 ~~ knomj_t2 0.242 0.007 0.007 0.025 0.025
174 coping_t2 =~ cope5_t1 0.239 0.070 0.035 0.034 0.034
791 rsmj4_t2 ~~ knomj_t2 0.237 -0.007 -0.007 -0.025 -0.025
561 cope3_t2 ~~ rsmj5_t1 0.232 0.020 0.020 0.034 0.034
885 coping_t2 ~ Refusal_t1 0.230 0.024 0.033 0.033 0.033
471 cope8_t1 ~~ knomj_t2 0.227 -0.012 -0.012 -0.029 -0.029
459 cope8_t1 ~~ rsmj1_t1 0.225 0.015 0.015 0.023 0.023
699 rsmj1_t1 ~~ peermj_t2 0.225 -0.009 -0.009 -0.020 -0.020
678 cope9_t2 ~~ rsmj1_t2 0.222 0.017 0.017 0.026 0.026
551 cope3_t2 ~~ cope4_t2 0.222 0.028 0.028 0.050 0.050
634 cope6_t2 ~~ attmj_t1 0.219 0.021 0.021 0.024 0.024
355 cope4_t1 ~~ attmj_t2 0.215 0.024 0.024 0.024 0.024
170 coping_t2 =~ cope1_t1 0.214 0.071 0.035 0.032 0.032
803 attmj_t2 ~~ knomj_t2 0.210 0.008 0.008 0.024 0.024
819 rsk5_t2 ~~ peermj_t1 0.205 0.010 0.010 0.021 0.021
260 cope1_t1 ~~ rsmj4_t2 0.205 0.019 0.019 0.024 0.024
799 rsmj5_t2 ~~ rsk5_t2 0.204 -0.009 -0.009 -0.029 -0.029
323 cope3_t1 ~~ rsmj5_t2 0.203 0.016 0.016 0.036 0.036
656 cope8_t2 ~~ rsmj1_t1 0.202 0.013 0.013 0.022 0.022
753 rsmj5_t1 ~~ peermj_t2 0.200 -0.013 -0.013 -0.025 -0.025
273 cope2_t1 ~~ cope8_t1 0.198 -0.032 -0.032 -0.027 -0.027
401 cope6_t1 ~~ cope7_t2 0.195 -0.025 -0.025 -0.025 -0.025
291 cope2_t1 ~~ rsmj4_t2 0.195 -0.017 -0.017 -0.022 -0.022
933 knomj_t1 ~ attmj_t2 0.193 0.010 0.010 0.024 0.024
267 cope1_t1 ~~ attmj_t1 0.192 -0.022 -0.022 -0.021 -0.021
437 cope7_t1 ~~ rsmj1_t2 0.191 0.016 0.016 0.023 0.023
772 rsmj2_t2 ~~ attmj_t2 0.191 -0.012 -0.012 -0.026 -0.026
730 rsmj3_t1 ~~ rsk5_t2 0.190 0.008 0.008 0.034 0.034
182 coping_t2 =~ rsmj4_t1 0.182 0.030 0.015 0.016 0.016
823 coping_t1 ~~ Refusal_t2 0.180 0.003 0.036 0.036 0.036
164 coping_t1 =~ rsmj5_t1 0.179 -0.169 -0.026 -0.023 -0.023
542 cope2_t2 ~~ rsmj4_t2 0.179 0.018 0.018 0.022 0.022
897 Refusal_t2 ~ coping_t1 0.178 0.112 0.029 0.029 0.029
354 cope4_t1 ~~ rsmj5_t2 0.172 -0.017 -0.017 -0.028 -0.028
455 cope8_t1 ~~ cope6_t2 0.168 0.026 0.026 0.026 0.026
313 cope3_t1 ~~ cope9_t2 0.167 -0.024 -0.024 -0.029 -0.029
543 cope2_t2 ~~ rsmj5_t2 0.159 -0.016 -0.016 -0.026 -0.026
156 coping_t1 =~ cope6_t2 0.154 0.209 0.033 0.029 0.029
733 rsmj3_t1 ~~ peermj_t1 0.152 -0.009 -0.009 -0.028 -0.028
303 cope3_t1 ~~ cope8_t1 0.148 -0.051 -0.051 -0.057 -0.057
296 cope2_t1 ~~ usemj1_t2 0.146 0.014 0.014 0.021 0.021
787 rsmj3_t2 ~~ peermj_t1 0.145 -0.008 -0.008 -0.021 -0.021
277 cope2_t1 ~~ cope4_t2 0.144 0.018 0.018 0.023 0.023
568 cope3_t2 ~~ peermj_t2 0.143 -0.012 -0.012 -0.022 -0.022
846 peermj_t2 ~ knomj_t1 0.136 0.034 0.034 0.018 0.044
235 cope1_t1 ~~ cope2_t1 0.132 0.024 0.024 0.020 0.020
305 cope3_t1 ~~ cope1_t2 0.131 0.018 0.018 0.026 0.026
716 rsmj2_t1 ~~ rsk5_t2 0.131 -0.010 -0.010 -0.021 -0.021
784 rsmj3_t2 ~~ rsk5_t2 0.127 -0.006 -0.006 -0.024 -0.024
177 coping_t2 =~ cope8_t1 0.124 -0.058 -0.029 -0.025 -0.025
436 cope7_t1 ~~ rsmj5_t1 0.124 -0.017 -0.017 -0.022 -0.022
181 coping_t2 =~ rsmj3_t1 0.121 -0.027 -0.014 -0.013 -0.013
754 rsmj5_t1 ~~ knomj_t2 0.118 0.006 0.006 0.021 0.021
231 Refusal_t2 =~ rsmj2_t1 0.118 0.037 0.022 0.020 0.020
641 cope7_t2 ~~ rsmj4_t1 0.116 -0.010 -0.010 -0.015 -0.015
466 cope8_t1 ~~ rsmj3_t2 0.116 0.012 0.012 0.024 0.024
165 coping_t1 =~ rsmj1_t2 0.115 0.102 0.016 0.018 0.018
353 cope4_t1 ~~ rsmj4_t2 0.115 0.015 0.015 0.018 0.018
817 rsk5_t2 ~~ usemj1_t2 0.108 -0.011 -0.011 -0.032 -0.032
971 coping_t1 ~ rsk5_t1 0.108 0.005 0.033 0.026 0.033
613 cope5_t2 ~~ usemj1_t2 0.108 -0.012 -0.012 -0.018 -0.018
442 cope7_t1 ~~ attmj_t2 0.108 0.016 0.016 0.017 0.017
938 knomj_t1 ~ Refusal_t2 0.106 0.012 0.007 0.018 0.018
578 cope4_t2 ~~ cope9_t2 0.106 0.017 0.017 0.025 0.025
735 rsmj4_t1 ~~ rsmj1_t2 0.102 -0.006 -0.006 -0.013 -0.013
508 cope1_t2 ~~ cope8_t2 0.096 0.016 0.016 0.020 0.020
256 cope1_t1 ~~ rsmj5_t1 0.096 0.015 0.015 0.019 0.019
332 cope4_t1 ~~ cope6_t1 0.094 0.022 0.022 0.020 0.020
343 cope4_t1 ~~ cope8_t2 0.093 0.019 0.019 0.018 0.018
653 cope7_t2 ~~ attmj_t1 0.093 0.013 0.013 0.014 0.014
346 cope4_t1 ~~ rsmj2_t1 0.092 -0.016 -0.016 -0.018 -0.018
452 cope8_t1 ~~ cope3_t2 0.090 -0.017 -0.017 -0.020 -0.020
377 cope5_t1 ~~ rsmj3_t1 0.089 0.010 0.010 0.024 0.024
640 cope7_t2 ~~ rsmj3_t1 0.088 0.010 0.010 0.023 0.023
604 cope5_t2 ~~ rsmj1_t2 0.087 0.011 0.011 0.015 0.015
390 cope5_t1 ~~ attmj_t1 0.086 0.014 0.014 0.014 0.014
207 Refusal_t1 =~ rsmj1_t2 0.084 0.019 0.013 0.015 0.015
338 cope4_t1 ~~ cope3_t2 0.084 -0.017 -0.017 -0.019 -0.019
214 Refusal_t2 =~ cope3_t1 0.083 0.031 0.018 0.017 0.017
944 knomj_t1 ~ Refusal_t1 0.082 0.010 0.007 0.016 0.016
673 cope9_t2 ~~ rsmj1_t1 0.081 -0.009 -0.009 -0.014 -0.014
659 cope8_t2 ~~ rsmj4_t1 0.079 0.008 0.008 0.013 0.013
351 cope4_t1 ~~ rsmj2_t2 0.077 0.011 0.011 0.018 0.018
752 rsmj5_t1 ~~ attmj_t2 0.076 0.010 0.010 0.015 0.015
665 cope8_t2 ~~ rsmj5_t2 0.073 -0.009 -0.009 -0.019 -0.019
179 coping_t2 =~ rsmj1_t1 0.071 0.018 0.009 0.010 0.010
266 cope1_t1 ~~ usemj1_t2 0.071 -0.010 -0.010 -0.015 -0.015
311 cope3_t1 ~~ cope7_t2 0.069 0.015 0.015 0.017 0.017
588 cope4_t2 ~~ rsmj5_t2 0.069 -0.007 -0.007 -0.020 -0.020
626 cope6_t2 ~~ rsmj3_t2 0.068 0.008 0.008 0.019 0.019
292 cope2_t1 ~~ rsmj5_t2 0.068 -0.010 -0.010 -0.016 -0.016
940 knomj_t1 ~ attmj_t1 0.065 -0.006 -0.006 -0.014 -0.014
419 cope6_t1 ~~ attmj_t1 0.065 0.012 0.012 0.013 0.013
479 cope9_t1 ~~ cope4_t2 0.064 -0.012 -0.012 -0.017 -0.017
163 coping_t1 =~ rsmj4_t1 0.064 0.067 0.010 0.011 0.011
895 Refusal_t2 ~ knomj_t1 0.062 0.020 0.033 0.013 0.033
268 cope1_t1 ~~ peermj_t1 0.062 -0.010 -0.010 -0.012 -0.012
487 cope9_t1 ~~ rsmj3_t1 0.061 0.009 0.009 0.020 0.020
966 coping_t1 ~ Refusal_t2 0.060 0.006 0.024 0.024 0.024
931 peermj_t1 ~ usemj1_t1 0.058 0.010 0.010 0.011 0.012
417 cope6_t1 ~~ rsk5_t2 0.058 0.008 0.008 0.015 0.015
433 cope7_t1 ~~ rsmj2_t1 0.056 -0.012 -0.012 -0.014 -0.014
546 cope2_t2 ~~ knomj_t2 0.055 -0.006 -0.006 -0.013 -0.013
992 usemj1_t1 ~ rsk5_t2 0.052 0.013 0.013 0.010 0.010
726 rsmj3_t1 ~~ rsmj5_t2 0.051 0.005 0.005 0.021 0.021
603 cope5_t2 ~~ rsmj5_t1 0.049 0.011 0.011 0.013 0.013
583 cope4_t2 ~~ rsmj5_t1 0.047 -0.008 -0.008 -0.015 -0.015
848 peermj_t2 ~ coping_t1 0.047 0.067 0.010 0.014 0.014
929 peermj_t1 ~ coping_t1 0.046 0.074 0.012 0.014 0.014
972 coping_t1 ~ Refusal_t1 0.046 0.013 0.058 0.058 0.058
426 cope7_t1 ~~ cope4_t2 0.045 0.010 0.010 0.014 0.014
930 peermj_t1 ~ Refusal_t1 0.045 -1.383 -0.955 -1.182 -1.182
562 cope3_t2 ~~ rsmj1_t2 0.044 0.007 0.007 0.012 0.012
302 cope3_t1 ~~ cope7_t1 0.042 -0.016 -0.016 -0.017 -0.017
629 cope6_t2 ~~ attmj_t2 0.041 -0.009 -0.009 -0.011 -0.011
329 cope3_t1 ~~ attmj_t1 0.041 -0.009 -0.009 -0.012 -0.012
902 usemj1_t2 ~ rsk5_t1 0.041 0.012 0.012 0.014 0.018
792 rsmj4_t2 ~~ rsk5_t2 0.040 -0.004 -0.004 -0.010 -0.010
274 cope2_t1 ~~ cope9_t1 0.039 0.013 0.013 0.011 0.011
483 cope9_t1 ~~ cope8_t2 0.039 0.012 0.012 0.012 0.012
901 usemj1_t2 ~ knomj_t1 0.038 0.018 0.018 0.011 0.028
814 knomj_t2 ~~ usemj1_t2 0.038 -0.017 -0.017 -0.070 -0.070
286 cope2_t1 ~~ rsmj4_t1 0.034 -0.006 -0.006 -0.008 -0.008
330 cope3_t1 ~~ peermj_t1 0.033 -0.007 -0.007 -0.010 -0.010
388 cope5_t1 ~~ rsk5_t2 0.033 -0.006 -0.006 -0.010 -0.010
610 cope5_t2 ~~ peermj_t2 0.033 -0.007 -0.007 -0.009 -0.009
882 coping_t2 ~ peermj_t1 0.032 -0.007 -0.014 -0.012 -0.012
558 cope3_t2 ~~ rsmj2_t1 0.030 0.007 0.007 0.012 0.012
798 rsmj5_t2 ~~ knomj_t2 0.029 -0.002 -0.002 -0.011 -0.011
936 knomj_t1 ~ rsk5_t2 0.029 0.004 0.004 0.008 0.008
554 cope3_t2 ~~ cope7_t2 0.029 0.009 0.009 0.011 0.011
399 cope6_t1 ~~ cope5_t2 0.028 0.010 0.010 0.009 0.009
304 cope3_t1 ~~ cope9_t1 0.026 0.012 0.012 0.014 0.014
776 rsmj2_t2 ~~ usemj1_t2 0.026 0.003 0.003 0.011 0.011
456 cope8_t1 ~~ cope7_t2 0.024 -0.010 -0.010 -0.009 -0.009
780 rsmj3_t2 ~~ rsmj5_t2 0.024 0.005 0.005 0.020 0.020
622 cope6_t2 ~~ rsmj4_t1 0.024 -0.005 -0.005 -0.007 -0.007
409 cope6_t1 ~~ rsmj1_t2 0.024 0.005 0.005 0.008 0.008
519 cope1_t2 ~~ rsmj5_t2 0.022 0.005 0.005 0.010 0.010
816 knomj_t2 ~~ peermj_t1 0.022 0.002 0.002 0.007 0.007
924 peermj_t1 ~ Refusal_t2 0.021 -0.012 -0.007 -0.009 -0.009
701 rsmj1_t1 ~~ rsk5_t2 0.021 0.002 0.002 0.006 0.006
892 Refusal_t2 ~ usemj1_t2 0.020 -0.011 -0.019 -0.012 -0.012
1004 rapd ~ peermj_t2 0.019 -0.003 -0.003 -0.013 -0.013
345 cope4_t1 ~~ rsmj1_t1 0.019 -0.005 -0.005 -0.006 -0.006
350 cope4_t1 ~~ rsmj1_t2 0.017 -0.005 -0.005 -0.007 -0.007
989 usemj1_t1 ~ attmj_t2 0.016 -0.006 -0.006 -0.007 -0.007
276 cope2_t1 ~~ cope3_t2 0.014 -0.007 -0.007 -0.007 -0.007
430 cope7_t1 ~~ cope8_t2 0.013 -0.007 -0.007 -0.007 -0.007
349 cope4_t1 ~~ rsmj5_t1 0.013 0.006 0.006 0.007 0.007
210 Refusal_t1 =~ rsmj4_t2 0.013 0.008 0.006 0.006 0.006
721 rsmj3_t1 ~~ rsmj5_t1 0.012 -0.005 -0.005 -0.016 -0.016
969 coping_t1 ~ peermj_t1 0.012 -0.002 -0.010 -0.008 -0.008
731 rsmj3_t1 ~~ usemj1_t2 0.011 0.002 0.002 0.008 0.008
515 cope1_t2 ~~ rsmj1_t2 0.011 -0.003 -0.003 -0.006 -0.006
439 cope7_t1 ~~ rsmj3_t2 0.011 0.004 0.004 0.007 0.007
275 cope2_t1 ~~ cope1_t2 0.010 -0.005 -0.005 -0.006 -0.006
259 cope1_t1 ~~ rsmj3_t2 0.009 0.003 0.003 0.007 0.007
414 cope6_t1 ~~ attmj_t2 0.009 0.004 0.004 0.005 0.005
412 cope6_t1 ~~ rsmj4_t2 0.008 -0.003 -0.003 -0.005 -0.005
239 cope1_t1 ~~ cope6_t1 0.008 0.006 0.006 0.006 0.006
404 cope6_t1 ~~ rsmj1_t1 0.007 -0.002 -0.002 -0.004 -0.004
571 cope3_t2 ~~ usemj1_t2 0.007 0.003 0.003 0.006 0.006
756 rsmj5_t1 ~~ usemj1_t2 0.007 0.002 0.002 0.005 0.005
609 cope5_t2 ~~ attmj_t2 0.007 -0.004 -0.004 -0.004 -0.004
314 cope3_t1 ~~ rsmj1_t1 0.005 -0.002 -0.002 -0.004 -0.004
485 cope9_t1 ~~ rsmj1_t1 0.005 0.002 0.002 0.003 0.003
962 coping_t1 ~ peermj_t2 0.005 -0.001 -0.007 -0.006 -0.006
871 rsk5_t2 ~ knomj_t1 0.005 0.006 0.006 0.003 0.008
602 cope5_t2 ~~ rsmj4_t1 0.004 0.002 0.002 0.003 0.003
579 cope4_t2 ~~ rsmj1_t1 0.004 -0.001 -0.001 -0.003 -0.003
710 rsmj2_t1 ~~ rsmj3_t2 0.004 -0.002 -0.002 -0.004 -0.004
838 attmj_t2 ~ usemj1_t1 0.003 -0.003 -0.003 -0.003 -0.003
530 cope2_t2 ~~ cope6_t2 0.003 -0.003 -0.003 -0.003 -0.003
642 cope7_t2 ~~ rsmj5_t1 0.003 0.002 0.002 0.003 0.003
1008 rapd ~ Refusal_t2 0.003 -0.001 -0.001 -0.005 -0.005
397 cope6_t1 ~~ cope3_t2 0.002 0.003 0.003 0.003 0.003
913 attmj_t1 ~ knomj_t1 0.002 0.005 0.005 0.002 0.005
540 cope2_t2 ~~ rsmj2_t2 0.002 -0.002 -0.002 -0.003 -0.003
689 cope9_t2 ~~ peermj_t1 0.002 0.002 0.002 0.002 0.002
582 cope4_t2 ~~ rsmj4_t1 0.001 -0.001 -0.001 -0.002 -0.002
991 usemj1_t1 ~ knomj_t2 0.001 -0.004 -0.004 -0.002 -0.002
573 cope3_t2 ~~ peermj_t1 0.001 -0.001 -0.001 -0.002 -0.002
874 rsk5_t2 ~ usemj1_t1 0.001 0.001 0.001 0.001 0.001
342 cope4_t1 ~~ cope7_t2 0.001 -0.002 -0.002 -0.002 -0.002
740 rsmj4_t1 ~~ attmj_t2 0.001 0.001 0.001 0.001 0.001
160 coping_t1 =~ rsmj1_t1 0.001 -0.007 -0.001 -0.001 -0.001
416 cope6_t1 ~~ knomj_t2 0.001 -0.001 -0.001 -0.001 -0.001
257 cope1_t1 ~~ rsmj1_t2 0.000 0.001 0.001 0.001 0.001
478 cope9_t1 ~~ cope3_t2 0.000 0.001 0.001 0.001 0.001
596 cope5_t2 ~~ cope6_t2 0.000 0.001 0.001 0.001 0.001
939 knomj_t1 ~ usemj1_t2 0.000 0.001 0.001 0.001 0.001
475 cope8_t1 ~~ peermj_t1 0.000 0.001 0.001 0.001 0.001
647 cope7_t2 ~~ rsmj5_t2 0.000 0.001 0.001 0.001 0.001
698 rsmj1_t1 ~~ attmj_t2 0.000 0.000 0.000 0.001 0.001
755 rsmj5_t1 ~~ rsk5_t2 0.000 0.000 0.000 0.001 0.001
513 cope1_t2 ~~ rsmj4_t1 0.000 0.000 0.000 -0.001 -0.001
382 cope5_t1 ~~ rsmj3_t2 0.000 0.000 0.000 -0.001 -0.001
191 Refusal_t1 =~ cope3_t1 0.000 0.001 0.001 0.001 0.001
743 rsmj4_t1 ~~ rsk5_t2 0.000 0.000 0.000 0.000 0.000
331 cope4_t1 ~~ cope5_t1 0.000 0.000 0.000 0.000 0.000
548 cope2_t2 ~~ usemj1_t2 0.000 0.000 0.000 0.000 0.000
107 rapd ~~ rapd 0.000 0.000 0.000 0.000 0.000
105 usemj1_t1 ~~ usemj1_t1 0.000 0.000 0.000 0.000 0.000
1012 rapd ~ knomj_t1 0.000 0.000 0.000 0.000 0.000
104 rsk5_t1 ~~ rapd 0.000 0.000 0.000 NA 0.000
960 rsk5_t1 ~ rapd 0.000 0.000 0.000 0.000 0.000
101 knomj_t1 ~~ rapd 0.000 0.000 0.000 NA 0.000
102 rsk5_t1 ~~ rsk5_t1 0.000 0.000 0.000 0.000 0.000
946 knomj_t1 ~ rapd 0.000 0.000 0.000 0.000 0.000
1013 rapd ~ rsk5_t1 0.000 0.000 0.000 0.000 0.000
106 usemj1_t1 ~~ rapd 0.000 0.000 0.000 NA 0.000
956 rsk5_t1 ~ knomj_t1 0.000 0.000 0.000 0.000 0.000
103 rsk5_t1 ~~ usemj1_t1 0.000 0.000 0.000 NA 0.000
99 knomj_t1 ~~ rsk5_t1 0.000 0.000 0.000 NA 0.000
998 usemj1_t1 ~ knomj_t1 0.000 0.000 0.000 0.000 0.000
999 usemj1_t1 ~ rsk5_t1 0.000 0.000 0.000 0.000 0.000
100 knomj_t1 ~~ usemj1_t1 0.000 0.000 0.000 NA 0.000
98 knomj_t1 ~~ knomj_t1 0.000 0.000 0.000 0.000 0.000
942 knomj_t1 ~ rsk5_t1 0.000 0.000 0.000 0.000 0.000
1002 usemj1_t1 ~ rapd 0.000 0.000 0.000 0.000 0.000
945 knomj_t1 ~ usemj1_t1 0.000 0.000 0.000 0.000 0.000
1016 rapd ~ usemj1_t1 0.000 0.000 0.000 0.000 0.000
959 rsk5_t1 ~ usemj1_t1 0.000 0.000 0.000 0.000 0.000table(Student_Data_Full_No_NA$usemj1_t2)
0 1 2 3
279 9 2 13 Now without the sample weights
MJ_Full_1 <- '
coping_t1 =~ cope1_t1 + cope2_t1 + cope3_t1 + cope4_t1 + cope5_t1 +
cope6_t1 + cope7_t1 + cope8_t1 + cope9_t1
coping_t2 =~ cope1_t2 + cope2_t2 + cope3_t2 + cope4_t2 + cope5_t2 +
cope6_t2 + cope7_t2 + cope8_t2 + cope9_t2
Refusal_t1 =~ rsmj1_t1 + rsmj2_t1 + rsmj3_t1 + rsmj4_t1 + rsmj5_t1
Refusal_t2 =~ rsmj1_t2 + rsmj2_t2 + rsmj3_t2 + rsmj4_t2 + rsmj5_t2
attmj_t2 ~ attmj_t1
peermj_t2 ~ peermj_t1
knomj_t2 ~ knomj_t1
rsk5_t2 ~ rsk5_t1
coping_t2 ~ coping_t1
Refusal_t2 ~ Refusal_t1
usemj1_t2 ~ usemj1_t1 + coping_t2 + Refusal_t2 + knomj_t2 + rsk5_t2 +
peermj_t2 + attmj_t2 + rapd
coping_t2 ~ rapd
Refusal_t2 ~ rapd
knomj_t2 ~ rapd
rsk5_t2 ~ rapd
peermj_t2 ~ rapd
attmj_t2 ~ rapd
###Model Updates##
rsmj1_t1 ~~ rsmj4_t1
peermj_t2 ~~ attmj_t2
rsmj1_t2 ~~ rsmj4_t2
Refusal_t1 ~~ peermj_t1
peermj_t1 ~~ attmj_t1
cope2_t1 ~~ cope2_t2
cope2_t1 ~~ cope6_t1
cope5_t2 ~~ cope7_t2
cope2_t1 ~~ rsk5_t2
'
MJ_Full_fit_1 <- sem(MJ_Full_1, data = Student_Data_Full_No_NA,
estimator = "mlr", mimic = "Mplus")
summary(MJ_Full_fit_1, fit.measures = TRUE)lavaan 0.6-19 ended normally after 176 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 128
Number of observations 303
Number of missing patterns 1
Model Test User Model:
Standard Scaled
Test Statistic 2350.439 2127.497
Degrees of freedom 677 677
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.105
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 5375.321 4659.955
Degrees of freedom 735 735
P-value 0.000 0.000
Scaling correction factor 1.154
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.639 0.630
Tucker-Lewis Index (TLI) 0.608 0.599
Robust Comparative Fit Index (CFI) 0.651
Robust Tucker-Lewis Index (TLI) 0.621
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -13366.319 -13366.319
Scaling correction factor 1.344
for the MLR correction
Loglikelihood unrestricted model (H1) -12191.099 -12191.099
Scaling correction factor 1.143
for the MLR correction
Akaike (AIC) 26988.638 26988.638
Bayesian (BIC) 27463.995 27463.995
Sample-size adjusted Bayesian (SABIC) 27058.047 27058.047
Root Mean Square Error of Approximation:
RMSEA 0.090 0.084
90 Percent confidence interval - lower 0.086 0.080
90 Percent confidence interval - upper 0.094 0.088
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 0.961
Robust RMSEA 0.088
90 Percent confidence interval - lower 0.084
90 Percent confidence interval - upper 0.092
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.999
Standardized Root Mean Square Residual:
SRMR 0.133 0.133
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|)
coping_t1 =~
cope1_t1 1.000
cope2_t1 -1.340 1.992 -0.673 0.501
cope3_t1 4.300 3.278 1.312 0.190
cope4_t1 1.335 0.727 1.836 0.066
cope5_t1 0.646 1.404 0.460 0.645
cope6_t1 3.215 2.685 1.198 0.231
cope7_t1 -0.702 1.552 -0.452 0.651
cope8_t1 2.934 2.297 1.278 0.201
cope9_t1 -0.151 0.886 -0.170 0.865
coping_t2 =~
cope1_t2 1.000
cope2_t2 0.275 0.176 1.566 0.117
cope3_t2 1.559 0.265 5.892 0.000
cope4_t2 1.373 0.177 7.748 0.000
cope5_t2 0.205 0.159 1.290 0.197
cope6_t2 1.265 0.227 5.567 0.000
cope7_t2 0.544 0.166 3.280 0.001
cope8_t2 1.001 0.194 5.164 0.000
cope9_t2 1.000 0.179 5.573 0.000
Refusal_t1 =~
rsmj1_t1 1.000
rsmj2_t1 1.152 0.131 8.807 0.000
rsmj3_t1 1.395 0.124 11.284 0.000
rsmj4_t1 1.003 0.056 17.855 0.000
rsmj5_t1 1.310 0.145 9.014 0.000
Refusal_t2 =~
rsmj1_t2 1.000
rsmj2_t2 1.434 0.153 9.355 0.000
rsmj3_t2 1.422 0.138 10.294 0.000
rsmj4_t2 0.992 0.096 10.372 0.000
rsmj5_t2 1.538 0.169 9.096 0.000
Regressions:
Estimate Std.Err z-value P(>|z|)
attmj_t2 ~
attmj_t1 0.414 0.079 5.257 0.000
peermj_t2 ~
peermj_t1 0.418 0.066 6.376 0.000
knomj_t2 ~
knomj_t1 0.172 0.069 2.499 0.012
rsk5_t2 ~
rsk5_t1 0.536 0.055 9.791 0.000
coping_t2 ~
coping_t1 0.760 0.632 1.203 0.229
Refusal_t2 ~
Refusal_t1 0.484 0.080 6.059 0.000
usemj1_t2 ~
usemj1_t1 0.018 0.039 0.472 0.637
coping_t2 0.135 0.091 1.486 0.137
Refusal_t2 -0.116 0.075 -1.542 0.123
knomj_t2 -0.077 0.093 -0.833 0.405
rsk5_t2 -0.108 0.072 -1.506 0.132
peermj_t2 -0.195 0.071 -2.741 0.006
attmj_t2 0.051 0.059 0.853 0.394
rapd -0.258 0.264 -0.975 0.329
coping_t2 ~
rapd -0.017 0.173 -0.097 0.923
Refusal_t2 ~
rapd 0.426 0.142 3.000 0.003
knomj_t2 ~
rapd 0.057 0.153 0.374 0.708
rsk5_t2 ~
rapd 0.069 0.192 0.361 0.718
peermj_t2 ~
rapd 0.231 0.300 0.769 0.442
attmj_t2 ~
rapd -0.336 0.264 -1.272 0.203
Covariances:
Estimate Std.Err z-value P(>|z|)
.rsmj1_t1 ~~
.rsmj4_t1 0.256 0.052 4.953 0.000
.attmj_t2 ~~
.peermj_t2 0.257 0.062 4.150 0.000
.rsmj1_t2 ~~
.rsmj4_t2 0.203 0.045 4.512 0.000
Refusal_t1 ~~
peermj_t1 0.137 0.041 3.376 0.001
attmj_t1 ~~
peermj_t1 0.393 0.064 6.121 0.000
.cope2_t1 ~~
.cope2_t2 0.150 0.071 2.108 0.035
.cope6_t1 -0.240 0.154 -1.557 0.119
.cope5_t2 ~~
.cope7_t2 0.335 0.067 4.977 0.000
.cope2_t1 ~~
.rsk5_t2 0.135 0.039 3.437 0.001
coping_t1 ~~
Refusal_t1 -0.001 0.011 -0.117 0.907
Intercepts:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 2.502 0.063 39.527 0.000
.cope2_t1 2.469 0.065 37.806 0.000
.cope3_t1 2.822 0.062 45.808 0.000
.cope4_t1 2.769 0.067 41.444 0.000
.cope5_t1 1.990 0.059 33.869 0.000
.cope6_t1 2.917 0.063 46.530 0.000
.cope7_t1 2.531 0.062 40.682 0.000
.cope8_t1 2.376 0.066 35.772 0.000
.cope9_t1 2.667 0.062 42.985 0.000
.cope1_t2 2.812 0.174 16.172 0.000
.cope2_t2 2.473 0.081 30.365 0.000
.cope3_t2 2.629 0.266 9.889 0.000
.cope4_t2 2.989 0.238 12.542 0.000
.cope5_t2 2.257 0.075 30.295 0.000
.cope6_t2 2.915 0.223 13.077 0.000
.cope7_t2 2.428 0.109 22.368 0.000
.cope8_t2 2.280 0.179 12.729 0.000
.cope9_t2 2.653 0.176 15.097 0.000
.rsmj1_t1 3.426 0.054 63.634 0.000
.rsmj2_t1 3.056 0.064 47.752 0.000
.rsmj3_t1 3.165 0.060 52.337 0.000
.rsmj4_t1 3.413 0.055 61.856 0.000
.rsmj5_t1 2.977 0.067 44.393 0.000
.rsmj1_t2 3.061 0.153 19.949 0.000
.rsmj2_t2 2.623 0.183 14.328 0.000
.rsmj3_t2 2.683 0.190 14.142 0.000
.rsmj4_t2 3.051 0.156 19.617 0.000
.rsmj5_t2 2.563 0.203 12.625 0.000
.attmj_t2 2.805 0.408 6.870 0.000
.peermj_t2 1.248 0.313 3.991 0.000
.knomj_t2 0.589 0.147 4.004 0.000
.rsk5_t2 1.128 0.223 5.052 0.000
.usemj1_t2 1.057 0.347 3.044 0.002
attmj_t1 4.363 0.054 81.047 0.000
peermj_t1 2.419 0.048 49.901 0.000
Variances:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 1.189 0.065 18.348 0.000
.cope2_t1 1.239 0.120 10.314 0.000
.cope3_t1 0.702 0.198 3.546 0.000
.cope4_t1 1.309 0.076 17.144 0.000
.cope5_t1 1.036 0.074 14.010 0.000
.cope6_t1 0.941 0.182 5.159 0.000
.cope7_t1 1.161 0.076 15.356 0.000
.cope8_t1 1.128 0.122 9.274 0.000
.cope9_t1 1.166 0.059 19.721 0.000
.cope1_t2 0.715 0.073 9.865 0.000
.cope2_t2 1.272 0.061 20.691 0.000
.cope3_t2 0.651 0.079 8.224 0.000
.cope4_t2 0.479 0.064 7.535 0.000
.cope5_t2 1.255 0.060 20.945 0.000
.cope6_t2 0.882 0.083 10.644 0.000
.cope7_t2 1.016 0.063 16.166 0.000
.cope8_t2 0.852 0.076 11.251 0.000
.cope9_t2 0.995 0.080 12.424 0.000
.rsmj1_t1 0.401 0.052 7.727 0.000
.rsmj2_t1 0.608 0.092 6.587 0.000
.rsmj3_t1 0.179 0.042 4.268 0.000
.rsmj4_t1 0.442 0.062 7.075 0.000
.rsmj5_t1 0.543 0.081 6.733 0.000
.rsmj1_t2 0.428 0.057 7.473 0.000
.rsmj2_t2 0.294 0.050 5.891 0.000
.rsmj3_t2 0.216 0.042 5.092 0.000
.rsmj4_t2 0.513 0.067 7.647 0.000
.rsmj5_t2 0.284 0.048 5.974 0.000
.attmj_t2 0.749 0.102 7.375 0.000
.peermj_t2 0.469 0.054 8.605 0.000
.knomj_t2 0.165 0.013 12.513 0.000
.rsk5_t2 0.341 0.040 8.470 0.000
.usemj1_t2 0.354 0.081 4.358 0.000
attmj_t1 0.878 0.105 8.368 0.000
peermj_t1 0.654 0.061 10.687 0.000
coping_t1 0.024 0.035 0.697 0.486
.coping_t2 0.232 0.066 3.536 0.000
Refusal_t1 0.477 0.095 5.034 0.000
.Refusal_t2 0.237 0.056 4.217 0.000Now by group:
MJ_Full_2 <- '
##Latent Variables##
coping_t1 =~ cope1_t1 + cope2_t1 + cope3_t1 + cope4_t1 + cope5_t1 +
cope6_t1 + cope7_t1 + cope8_t1 + cope9_t1
coping_t2 =~ cope1_t2 + cope2_t2 + cope3_t2 + cope4_t2 + cope5_t2 +
cope6_t2 + cope7_t2 + cope8_t2 + cope9_t2
Refusal_t1 =~ rsmj1_t1 + rsmj2_t1 + rsmj3_t1 + rsmj4_t1 + rsmj5_t1
Refusal_t2 =~ rsmj1_t2 + rsmj2_t2 + rsmj3_t2 + rsmj4_t2 + rsmj5_t2
##Regressions
attmj_t2 ~ attmj_t1
peermj_t2 ~ peermj_t1
knomj_t2 ~ knomj_t1
rsk5_t2 ~ rsk5_t1
coping_t2 ~ coping_t1
Refusal_t2 ~ Refusal_t1
usemj1_t2 ~ usemj1_t1 + coping_t2 + Refusal_t2 + knomj_t2 + rsk5_t2 +
peermj_t2 + attmj_t2
'
MJ_Full_fit_2 <- sem(MJ_Full_2, data = Student_Data_Full, estimator = "mlr", #sampling.weights = "ipw",
mimic = "Mplus",group = "rapd")Warning: lavaan->lav_model_vcov():
The variance-covariance matrix of the estimated parameters (vcov) does not
appear to be positive definite! The smallest eigenvalue (= 1.103575e-12)
is close to zero. This may be a symptom that the model is not identified.summary(MJ_Full_fit_2, fit.measures = TRUE, standardized = TRUE)lavaan 0.6-19 ended normally after 136 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 220
Number of equality constraints 57
Number of observations per group:
0 54
1 292
Number of missing patterns per group:
0 1
1 1
Model Test User Model:
Standard Scaled
Test Statistic 4032.195 3972.134
Degrees of freedom 1355 1355
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.015
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
0 1506.519 1506.519
1 2465.616 2465.616
Model Test Baseline Model:
Test statistic 6895.469 6463.626
Degrees of freedom 1386 1386
P-value 0.000 0.000
Scaling correction factor 1.067
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.514 0.485
Tucker-Lewis Index (TLI) 0.503 0.473
Robust Comparative Fit Index (CFI) 0.520
Robust Tucker-Lewis Index (TLI) 0.509
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -14672.203 -14672.203
Scaling correction factor 1.042
for the MLR correction
Loglikelihood unrestricted model (H1) -12656.106 -12656.106
Scaling correction factor 1.057
for the MLR correction
Akaike (AIC) 29670.407 29670.407
Bayesian (BIC) 30297.377 30297.377
Sample-size adjusted Bayesian (SABIC) 29780.293 29780.293
Root Mean Square Error of Approximation:
RMSEA 0.107 0.106
90 Percent confidence interval - lower 0.103 0.102
90 Percent confidence interval - upper 0.111 0.109
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 1.000
Robust RMSEA 0.106
90 Percent confidence interval - lower 0.102
90 Percent confidence interval - upper 0.110
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 1.000
Standardized Root Mean Square Residual:
SRMR 0.136 0.136
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Group 1 [0]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
coping_t1 =~
cop1_t1 1.000 0.379 0.369
cop2_t1 (.p2.) -0.456 2.457 -0.186 0.853 -0.173 -0.168
cop3_t1 (.p3.) 1.636 2.645 0.619 0.536 0.621 0.456
cop4_t1 (.p4.) 0.946 0.449 2.108 0.035 0.359 0.350
cop5_t1 (.p5.) 0.570 0.654 0.872 0.383 0.216 0.217
cop6_t1 (.p6.) 1.258 2.751 0.457 0.647 0.477 0.406
cop7_t1 (.p7.) 0.145 1.457 0.099 0.921 0.055 0.051
cop8_t1 (.p8.) 1.240 1.821 0.681 0.496 0.471 0.355
cop9_t1 (.p9.) 0.300 0.844 0.355 0.722 0.114 0.087
coping_t2 =~
cop1_t2 1.000 0.511 0.475
cop2_t2 (.11.) 0.381 0.179 2.129 0.033 0.194 0.153
cop3_t2 (.12.) 1.456 0.263 5.534 0.000 0.743 0.603
cop4_t2 (.13.) 1.341 0.154 8.689 0.000 0.685 0.589
cop5_t2 (.14.) 0.417 0.174 2.399 0.016 0.213 0.183
cop6_t2 (.15.) 1.205 0.227 5.301 0.000 0.615 0.545
cop7_t2 (.16.) 0.600 0.173 3.474 0.001 0.306 0.236
cop8_t2 (.17.) 0.951 0.183 5.194 0.000 0.486 0.332
cop9_t2 (.18.) 0.998 0.175 5.713 0.000 0.510 0.371
Refusal_t1 =~
rsmj1_1 1.000 0.836 0.708
rsmj2_1 (.20.) 1.058 0.153 6.934 0.000 0.884 0.776
rsmj3_1 (.21.) 1.246 0.163 7.624 0.000 1.041 0.921
rsmj4_1 (.22.) 1.010 0.045 22.271 0.000 0.844 0.697
rsmj5_1 (.23.) 1.149 0.184 6.238 0.000 0.960 0.743
Refusal_t2 =~
rsmj1_2 1.000 0.740 0.729
rsmj2_2 (.25.) 1.374 0.127 10.779 0.000 1.017 0.753
rsmj3_2 (.26.) 1.365 0.120 11.408 0.000 1.009 0.943
rsmj4_2 (.27.) 1.010 0.085 11.860 0.000 0.747 0.784
rsmj5_2 (.28.) 1.409 0.137 10.302 0.000 1.042 0.916
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
attmj_t2 ~
attmj_t1 0.510 0.076 6.670 0.000 0.510 0.453
peermj_t2 ~
peermj_t1 0.477 0.067 7.091 0.000 0.477 0.497
knomj_t2 ~
knomj_t1 0.222 0.086 2.570 0.010 0.222 0.240
rsk5_t2 ~
rsk5_t1 0.499 0.066 7.526 0.000 0.499 0.525
coping_t2 ~
coping_t1 1.232 2.529 0.487 0.626 0.915 0.915
Refusal_t2 ~
Refusal_t1 0.294 0.163 1.803 0.071 0.332 0.332
usemj1_t2 ~
usemj1_t1 0.076 0.087 0.881 0.379 0.076 0.124
coping_t2 -0.198 0.396 -0.501 0.616 -0.101 -0.135
Refusal_t2 -0.298 0.121 -2.454 0.014 -0.221 -0.293
knomj_t2 0.128 0.178 0.717 0.474 0.128 0.073
rsk5_t2 -0.218 0.142 -1.537 0.124 -0.218 -0.254
peermj_t2 -0.272 0.118 -2.307 0.021 -0.272 -0.314
attmj_t2 0.108 0.101 1.064 0.287 0.108 0.150
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
coping_t1 ~~
Refusal_t1 0.072 0.248 0.290 0.772 0.227 0.227
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.cop1_t1 (.95.) 2.666 0.210 12.708 0.000 2.666 2.597
.cop2_t1 (.96.) 2.357 0.205 11.487 0.000 2.357 2.292
.cop3_t1 (.97.) 3.017 0.169 17.836 0.000 3.017 2.214
.cop4_t1 (.98.) 2.921 0.151 19.353 0.000 2.921 2.846
.cop5_t1 (.99.) 2.086 0.181 11.491 0.000 2.086 2.090
.cop6_t1 (.100) 3.073 0.190 16.174 0.000 3.073 2.615
.cop7_t1 (.101) 2.553 0.211 12.105 0.000 2.553 2.387
.cop8_t1 (.102) 2.559 0.140 18.224 0.000 2.559 1.933
.cop9_t1 (.103) 2.698 0.166 16.251 0.000 2.698 2.069
.cop1_t2 (.104) 2.826 0.093 30.303 0.000 2.826 2.626
.cop2_t2 (.105) 2.499 0.071 35.087 0.000 2.499 1.972
.cop3_t2 (.106) 2.687 0.128 21.066 0.000 2.687 2.180
.cop4_t2 (.107) 3.033 0.117 25.920 0.000 3.033 2.608
.cop5_t2 (.108) 2.277 0.074 30.735 0.000 2.277 1.957
.cop6_t2 (.109) 2.945 0.113 26.164 0.000 2.945 2.608
.cop7_t2 (.110) 2.463 0.076 32.350 0.000 2.463 1.900
.cop8_t2 (.111) 2.319 0.097 23.989 0.000 2.319 1.584
.cop9_t2 (.112) 2.717 0.099 27.370 0.000 2.717 1.976
.rsmj1_1 (.113) 3.388 0.124 27.284 0.000 3.388 2.869
.rsmj2_1 (.114) 3.020 0.135 22.313 0.000 3.020 2.650
.rsmj3_1 (.115) 3.110 0.150 20.786 0.000 3.110 2.752
.rsmj4_1 (.116) 3.378 0.125 26.999 0.000 3.378 2.791
.rsmj5_1 (.117) 2.904 0.143 20.293 0.000 2.904 2.247
.rsmj1_2 (.118) 3.395 0.110 30.854 0.000 3.395 3.345
.rsmj2_2 (.119) 3.099 0.141 21.929 0.000 3.099 2.295
.rsmj3_2 (.120) 3.168 0.141 22.533 0.000 3.168 2.959
.rsmj4_2 (.121) 3.387 0.112 30.121 0.000 3.387 3.551
.rsmj5_2 (.122) 3.099 0.145 21.332 0.000 3.099 2.725
.attmj_2 (.123) 2.144 0.335 6.395 0.000 2.144 2.049
.prmj_t2 (.124) 1.323 0.158 8.380 0.000 1.323 1.525
.knmj_t2 (.125) 0.616 0.058 10.537 0.000 0.616 1.433
.rsk5_t2 (.126) 1.216 0.151 8.051 0.000 1.216 1.392
.usmj1_2 (.127) 0.718 0.204 3.525 0.000 0.718 0.954
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.cope1_t1 0.910 0.693 1.315 0.189 0.910 0.863
.cope2_t1 1.028 0.229 4.481 0.000 1.028 0.972
.cope3_t1 1.472 0.353 4.164 0.000 1.472 0.792
.cope4_t1 0.924 0.327 2.827 0.005 0.924 0.878
.cope5_t1 0.949 0.267 3.554 0.000 0.949 0.953
.cope6_t1 1.154 0.311 3.706 0.000 1.154 0.835
.cope7_t1 1.141 0.372 3.063 0.002 1.141 0.997
.cope8_t1 1.531 0.336 4.558 0.000 1.531 0.874
.cope9_t1 1.687 0.364 4.631 0.000 1.687 0.992
.cope1_t2 0.897 0.203 4.417 0.000 0.897 0.775
.cope2_t2 1.568 0.157 10.015 0.000 1.568 0.976
.cope3_t2 0.966 0.405 2.385 0.017 0.966 0.636
.cope4_t2 0.884 0.363 2.433 0.015 0.884 0.653
.cope5_t2 1.309 0.160 8.165 0.000 1.309 0.967
.cope6_t2 0.896 0.166 5.403 0.000 0.896 0.703
.cope7_t2 1.587 0.191 8.290 0.000 1.587 0.944
.cope8_t2 1.907 0.244 7.819 0.000 1.907 0.890
.cope9_t2 1.630 0.237 6.869 0.000 1.630 0.862
.rsmj1_t1 0.696 0.200 3.480 0.001 0.696 0.499
.rsmj2_t1 0.517 0.174 2.969 0.003 0.517 0.398
.rsmj3_t1 0.193 0.092 2.090 0.037 0.193 0.151
.rsmj4_t1 0.753 0.237 3.175 0.001 0.753 0.514
.rsmj5_t1 0.749 0.214 3.490 0.000 0.749 0.448
.rsmj1_t2 0.483 0.179 2.703 0.007 0.483 0.469
.rsmj2_t2 0.789 0.233 3.381 0.001 0.789 0.433
.rsmj3_t2 0.127 0.082 1.554 0.120 0.127 0.111
.rsmj4_t2 0.351 0.109 3.207 0.001 0.351 0.386
.rsmj5_t2 0.207 0.082 2.520 0.012 0.207 0.160
.attmj_t2 0.871 0.270 3.227 0.001 0.871 0.795
.peermj_t2 0.566 0.121 4.688 0.000 0.566 0.753
.knomj_t2 0.174 0.030 5.750 0.000 0.174 0.942
.rsk5_t2 0.553 0.161 3.440 0.001 0.553 0.725
.usemj1_t2 0.390 0.193 2.024 0.043 0.390 0.690
coping_t1 0.144 0.635 0.227 0.821 1.000 1.000
.coping_t2 0.043 0.126 0.339 0.734 0.163 0.163
Refusal_t1 0.698 0.196 3.562 0.000 1.000 1.000
.Refusal_t2 0.487 0.133 3.674 0.000 0.890 0.890
Group 2 [1]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
coping_t1 =~
cop1_t1 1.000 0.341 0.305
cop2_t1 (.p2.) -0.456 2.457 -0.186 0.853 -0.156 -0.138
cop3_t1 (.p3.) 1.636 2.645 0.619 0.536 0.559 0.532
cop4_t1 (.p4.) 0.946 0.449 2.108 0.035 0.323 0.275
cop5_t1 (.p5.) 0.570 0.654 0.872 0.383 0.195 0.190
cop6_t1 (.p6.) 1.258 2.751 0.457 0.647 0.429 0.398
cop7_t1 (.p7.) 0.145 1.457 0.099 0.921 0.049 0.045
cop8_t1 (.p8.) 1.240 1.821 0.681 0.496 0.423 0.372
cop9_t1 (.p9.) 0.300 0.844 0.355 0.722 0.102 0.096
coping_t2 =~
cop1_t2 1.000 0.513 0.527
cop2_t2 (.11.) 0.381 0.179 2.129 0.033 0.195 0.173
cop3_t2 (.12.) 1.456 0.263 5.534 0.000 0.746 0.683
cop4_t2 (.13.) 1.341 0.154 8.689 0.000 0.687 0.719
cop5_t2 (.14.) 0.417 0.174 2.399 0.016 0.214 0.189
cop6_t2 (.15.) 1.205 0.227 5.301 0.000 0.617 0.546
cop7_t2 (.16.) 0.600 0.173 3.474 0.001 0.307 0.297
cop8_t2 (.17.) 0.951 0.183 5.194 0.000 0.487 0.478
cop9_t2 (.18.) 0.998 0.175 5.713 0.000 0.512 0.468
Refusal_t1 =~
rsmj1_1 1.000 0.741 0.816
rsmj2_1 (.20.) 1.058 0.153 6.934 0.000 0.784 0.696
rsmj3_1 (.21.) 1.246 0.163 7.624 0.000 0.923 0.885
rsmj4_1 (.22.) 1.010 0.045 22.271 0.000 0.748 0.814
rsmj5_1 (.23.) 1.149 0.184 6.238 0.000 0.851 0.732
Refusal_t2 =~
rsmj1_2 1.000 0.614 0.714
rsmj2_2 (.25.) 1.374 0.127 10.779 0.000 0.844 0.851
rsmj3_2 (.26.) 1.365 0.120 11.408 0.000 0.838 0.879
rsmj4_2 (.27.) 1.010 0.085 11.860 0.000 0.621 0.676
rsmj5_2 (.28.) 1.409 0.137 10.302 0.000 0.866 0.836
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
attmj_t2 ~
attmj_t1 0.489 0.073 6.679 0.000 0.489 0.462
peermj_t2 ~
peermj_t1 0.480 0.058 8.313 0.000 0.480 0.504
knomj_t2 ~
knomj_t1 0.204 0.063 3.252 0.001 0.204 0.192
rsk5_t2 ~
rsk5_t1 0.530 0.053 10.007 0.000 0.530 0.556
coping_t2 ~
coping_t1 0.275 0.280 0.983 0.326 0.183 0.183
Refusal_t2 ~
Refusal_t1 0.437 0.084 5.212 0.000 0.527 0.527
usemj1_t2 ~
usemj1_t1 0.003 0.041 0.078 0.938 0.003 0.005
coping_t2 0.131 0.088 1.483 0.138 0.067 0.111
Refusal_t2 -0.109 0.073 -1.492 0.136 -0.067 -0.110
knomj_t2 -0.100 0.093 -1.079 0.281 -0.100 -0.068
rsk5_t2 -0.099 0.074 -1.330 0.183 -0.099 -0.114
peermj_t2 -0.146 0.069 -2.111 0.035 -0.146 -0.187
attmj_t2 0.035 0.056 0.619 0.536 0.035 0.056
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
coping_t1 ~~
Refusal_t1 0.006 0.027 0.231 0.817 0.025 0.025
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.cop1_t1 (.95.) 2.666 0.210 12.708 0.000 2.666 2.379
.cop2_t1 (.96.) 2.357 0.205 11.487 0.000 2.357 2.087
.cop3_t1 (.97.) 3.017 0.169 17.836 0.000 3.017 2.873
.cop4_t1 (.98.) 2.921 0.151 19.353 0.000 2.921 2.487
.cop5_t1 (.99.) 2.086 0.181 11.491 0.000 2.086 2.041
.cop6_t1 (.100) 3.073 0.190 16.174 0.000 3.073 2.848
.cop7_t1 (.101) 2.553 0.211 12.105 0.000 2.553 2.337
.cop8_t1 (.102) 2.559 0.140 18.224 0.000 2.559 2.249
.cop9_t1 (.103) 2.698 0.166 16.251 0.000 2.698 2.532
.cop1_t2 (.104) 2.826 0.093 30.303 0.000 2.826 2.908
.cop2_t2 (.105) 2.499 0.071 35.087 0.000 2.499 2.212
.cop3_t2 (.106) 2.687 0.128 21.066 0.000 2.687 2.458
.cop4_t2 (.107) 3.033 0.117 25.920 0.000 3.033 3.175
.cop5_t2 (.108) 2.277 0.074 30.735 0.000 2.277 2.011
.cop6_t2 (.109) 2.945 0.113 26.164 0.000 2.945 2.606
.cop7_t2 (.110) 2.463 0.076 32.350 0.000 2.463 2.378
.cop8_t2 (.111) 2.319 0.097 23.989 0.000 2.319 2.275
.cop9_t2 (.112) 2.717 0.099 27.370 0.000 2.717 2.483
.rsmj1_1 (.113) 3.388 0.124 27.284 0.000 3.388 3.732
.rsmj2_1 (.114) 3.020 0.135 22.313 0.000 3.020 2.682
.rsmj3_1 (.115) 3.110 0.150 20.786 0.000 3.110 2.981
.rsmj4_1 (.116) 3.378 0.125 26.999 0.000 3.378 3.677
.rsmj5_1 (.117) 2.904 0.143 20.293 0.000 2.904 2.499
.rsmj1_2 (.118) 3.395 0.110 30.854 0.000 3.395 3.944
.rsmj2_2 (.119) 3.099 0.141 21.929 0.000 3.099 3.125
.rsmj3_2 (.120) 3.168 0.141 22.533 0.000 3.168 3.322
.rsmj4_2 (.121) 3.387 0.112 30.121 0.000 3.387 3.688
.rsmj5_2 (.122) 3.099 0.145 21.332 0.000 3.099 2.993
.attmj_2 (.123) 2.144 0.335 6.395 0.000 2.144 2.209
.prmj_t2 (.124) 1.323 0.158 8.380 0.000 1.323 1.703
.knmj_t2 (.125) 0.616 0.058 10.537 0.000 0.616 1.498
.rsk5_t2 (.126) 1.216 0.151 8.051 0.000 1.216 1.731
.usmj1_2 (.127) 0.718 0.204 3.525 0.000 0.718 1.186
cpng_t1 -0.145 0.229 -0.633 0.527 -0.425 -0.425
.cpng_t2 -0.013 0.088 -0.152 0.879 -0.026 -0.026
Rfsl_t1 0.067 0.128 0.522 0.602 0.090 0.090
.Rfsl_t2 0.071 0.105 0.671 0.502 0.115 0.115
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.cope1_t1 1.140 0.197 5.774 0.000 1.140 0.907
.cope2_t1 1.251 0.304 4.110 0.000 1.251 0.981
.cope3_t1 0.791 0.347 2.277 0.023 0.791 0.717
.cope4_t1 1.275 0.171 7.437 0.000 1.275 0.924
.cope5_t1 1.007 0.160 6.310 0.000 1.007 0.964
.cope6_t1 0.980 0.456 2.148 0.032 0.980 0.842
.cope7_t1 1.191 0.059 20.246 0.000 1.191 0.998
.cope8_t1 1.115 0.137 8.167 0.000 1.115 0.862
.cope9_t1 1.126 0.075 14.970 0.000 1.126 0.991
.cope1_t2 0.682 0.073 9.350 0.000 0.682 0.722
.cope2_t2 1.238 0.064 19.337 0.000 1.238 0.970
.cope3_t2 0.638 0.081 7.922 0.000 0.638 0.534
.cope4_t2 0.441 0.068 6.498 0.000 0.441 0.483
.cope5_t2 1.237 0.063 19.752 0.000 1.237 0.964
.cope6_t2 0.896 0.084 10.634 0.000 0.896 0.701
.cope7_t2 0.978 0.067 14.708 0.000 0.978 0.912
.cope8_t2 0.801 0.074 10.858 0.000 0.801 0.771
.cope9_t2 0.935 0.078 12.063 0.000 0.935 0.781
.rsmj1_t1 0.275 0.089 3.097 0.002 0.275 0.334
.rsmj2_t1 0.653 0.103 6.354 0.000 0.653 0.515
.rsmj3_t1 0.236 0.063 3.775 0.000 0.236 0.217
.rsmj4_t1 0.285 0.095 2.998 0.003 0.285 0.337
.rsmj5_t1 0.627 0.121 5.176 0.000 0.627 0.464
.rsmj1_t2 0.364 0.056 6.513 0.000 0.364 0.491
.rsmj2_t2 0.271 0.046 5.834 0.000 0.271 0.275
.rsmj3_t2 0.206 0.037 5.600 0.000 0.206 0.227
.rsmj4_t2 0.458 0.067 6.804 0.000 0.458 0.543
.rsmj5_t2 0.323 0.051 6.314 0.000 0.323 0.301
.attmj_t2 0.741 0.101 7.326 0.000 0.741 0.787
.peermj_t2 0.450 0.055 8.178 0.000 0.450 0.746
.knomj_t2 0.163 0.014 11.991 0.000 0.163 0.963
.rsk5_t2 0.341 0.041 8.217 0.000 0.341 0.691
.usemj1_t2 0.336 0.084 4.010 0.000 0.336 0.919
coping_t1 0.116 0.229 0.508 0.611 1.000 1.000
.coping_t2 0.254 0.067 3.765 0.000 0.966 0.966
Refusal_t1 0.549 0.126 4.361 0.000 1.000 1.000
.Refusal_t2 0.273 0.060 4.552 0.000 0.722 0.722This model is for vaping which might yield better results given its being the drug of choice for many adolescents and easier to mask.
Vaping_Full <- '
##Latent Variables##
coping_t1 =~ cope1_t1 + cope2_t1 + cope3_t1 + cope4_t1 + cope5_t1 +
cope6_t1 + cope7_t1 + cope8_t1 + cope9_t1
coping_t2 =~ cope1_t2 + cope2_t2 + cope3_t2 + cope4_t2 + cope5_t2 +
cope6_t2 + cope7_t2 + cope8_t2 + cope9_t2
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
##Regressions
attnic_t2 ~ attnic_t1
#peermj_t2 ~ peermj_t1## Unknown peer use of vaping variable
knovap_t2 ~ knovap_t1
rsk1_t2 ~ rsk1_t1
coping_t2 ~ coping_t1
Refusal_t2 ~ Refusal_t1
usevap1_t2 ~ usevap1_t1 +coping_t2 + Refusal_t2 + knovap_t2 + rsk1_t2 +
attnic_t2 + rapd
coping_t2 ~ rapd
Refusal_t2 ~ rapd
knovap_t2 ~ rapd
rsk1_t2 ~ rapd
attnic_t2 ~ rapd
'
Vaping_Full_fit <- sem(Vaping_Full, data = Student_Data_Full_No_NA, estimator = "mlr",
sampling.weights = "ipw",
mimic = "Mplus")
summary(Vaping_Full_fit, fit.measures = TRUE)lavaan 0.6-19 ended normally after 391 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 110
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 2504.050 2314.300
Degrees of freedom 610 610
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.082
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 4616.931 4027.294
Degrees of freedom 656 656
P-value 0.000 0.000
Scaling correction factor 1.146
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.522 0.494
Tucker-Lewis Index (TLI) 0.486 0.456
Robust Comparative Fit Index (CFI) 0.531
Robust Tucker-Lewis Index (TLI) 0.495
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -12361.844 -12361.844
Scaling correction factor 1.524
for the MLR correction
Loglikelihood unrestricted model (H1) -11109.819 -11109.819
Scaling correction factor 1.150
for the MLR correction
Akaike (AIC) 24943.688 24943.688
Bayesian (BIC) 25352.198 25352.198
Sample-size adjusted Bayesian (SABIC) 25003.336 25003.336
Root Mean Square Error of Approximation:
RMSEA 0.101 0.096
90 Percent confidence interval - lower 0.097 0.092
90 Percent confidence interval - upper 0.105 0.100
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 1.000
Robust RMSEA 0.099
90 Percent confidence interval - lower 0.095
90 Percent confidence interval - upper 0.104
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 1.000
Standardized Root Mean Square Residual:
SRMR 0.114 0.114
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|)
coping_t1 =~
cope1_t1 1.000
cope2_t1 -15.867 34.977 -0.454 0.650
cope3_t1 5.572 10.418 0.535 0.593
cope4_t1 -0.155 3.184 -0.049 0.961
cope5_t1 -6.992 15.403 -0.454 0.650
cope6_t1 9.137 17.852 0.512 0.609
cope7_t1 -9.180 19.265 -0.477 0.634
cope8_t1 3.645 7.165 0.509 0.611
cope9_t1 -2.359 5.366 -0.440 0.660
coping_t2 =~
cope1_t2 1.000
cope2_t2 0.329 0.184 1.782 0.075
cope3_t2 1.536 0.261 5.878 0.000
cope4_t2 1.398 0.179 7.804 0.000
cope5_t2 0.261 0.171 1.526 0.127
cope6_t2 1.252 0.229 5.464 0.000
cope7_t2 0.568 0.179 3.165 0.002
cope8_t2 0.965 0.188 5.126 0.000
cope9_t2 1.016 0.186 5.470 0.000
Refusal_t1 =~
rsvap1_t1 1.000
rsvap2_t1 0.801 0.110 7.307 0.000
rsvap3_t1 0.947 0.097 9.737 0.000
rsvap4_t1 0.957 0.039 24.838 0.000
rsvap5_t1 0.736 0.113 6.509 0.000
Refusal_t2 =~
rsvap1_t2 1.000
rsvap2_t2 1.002 0.216 4.647 0.000
rsvap3_t2 0.946 0.216 4.381 0.000
rsvap4_t2 1.041 0.056 18.566 0.000
rsvap5_t2 0.936 0.240 3.895 0.000
Regressions:
Estimate Std.Err z-value P(>|z|)
attnic_t2 ~
attnic_t1 0.456 0.082 5.558 0.000
knovap_t2 ~
knovap_t1 0.071 0.112 0.638 0.524
rsk1_t2 ~
rsk1_t1 0.293 0.069 4.251 0.000
coping_t2 ~
coping_t1 0.207 1.236 0.167 0.867
Refusal_t2 ~
Refusal_t1 0.424 0.081 5.228 0.000
usevap1_t2 ~
usevap1_t1 -0.037 0.026 -1.456 0.145
coping_t2 0.136 0.097 1.403 0.161
Refusal_t2 -0.255 0.079 -3.249 0.001
knovap_t2 -0.219 0.290 -0.754 0.451
rsk1_t2 -0.064 0.066 -0.964 0.335
attnic_t2 -0.036 0.056 -0.642 0.521
rapd -0.334 0.280 -1.196 0.232
coping_t2 ~
rapd -0.027 0.192 -0.141 0.888
Refusal_t2 ~
rapd 0.419 0.275 1.522 0.128
knovap_t2 ~
rapd 0.049 0.093 0.523 0.601
rsk1_t2 ~
rapd 0.334 0.267 1.253 0.210
attnic_t2 ~
rapd 0.047 0.265 0.178 0.858
Covariances:
Estimate Std.Err z-value P(>|z|)
coping_t1 ~~
Refusal_t1 -0.003 0.008 -0.349 0.727
Intercepts:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 2.502 0.063 39.527 0.000
.cope2_t1 2.469 0.065 37.806 0.000
.cope3_t1 2.822 0.062 45.808 0.000
.cope4_t1 2.769 0.067 41.444 0.000
.cope5_t1 1.990 0.059 33.869 0.000
.cope6_t1 2.917 0.063 46.530 0.000
.cope7_t1 2.531 0.062 40.682 0.000
.cope8_t1 2.376 0.066 35.772 0.000
.cope9_t1 2.667 0.062 42.985 0.000
.cope1_t2 2.822 0.191 14.773 0.000
.cope2_t2 2.477 0.091 27.191 0.000
.cope3_t2 2.644 0.291 9.092 0.000
.cope4_t2 3.004 0.267 11.268 0.000
.cope5_t2 2.261 0.083 27.213 0.000
.cope6_t2 2.927 0.242 12.096 0.000
.cope7_t2 2.434 0.122 20.019 0.000
.cope8_t2 2.289 0.190 12.051 0.000
.cope9_t2 2.664 0.197 13.525 0.000
.rsvap1_t1 3.442 0.053 64.592 0.000
.rsvap2_t1 2.974 0.065 45.872 0.000
.rsvap3_t1 3.122 0.059 52.517 0.000
.rsvap4_t1 3.439 0.052 65.820 0.000
.rsvap5_t1 2.954 0.066 44.786 0.000
.rsvap1_t2 3.029 0.276 10.990 0.000
.rsvap2_t2 2.741 0.276 9.947 0.000
.rsvap3_t2 2.886 0.268 10.759 0.000
.rsvap4_t2 3.006 0.282 10.662 0.000
.rsvap5_t2 2.778 0.267 10.401 0.000
.attnic_t2 2.251 0.430 5.228 0.000
.knovap_t2 0.851 0.118 7.218 0.000
.rsk1_t2 1.415 0.334 4.239 0.000
.usevap1_t2 1.161 0.496 2.339 0.019
Variances:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 1.211 0.058 20.832 0.000
.cope2_t1 0.658 0.291 2.261 0.024
.cope3_t1 1.072 0.100 10.751 0.000
.cope4_t1 1.353 0.063 21.376 0.000
.cope5_t1 0.923 0.093 9.887 0.000
.cope6_t1 0.981 0.147 6.674 0.000
.cope7_t1 0.961 0.099 9.718 0.000
.cope8_t1 1.304 0.076 17.075 0.000
.cope9_t1 1.152 0.062 18.722 0.000
.cope1_t2 0.715 0.072 9.915 0.000
.cope2_t2 1.265 0.063 20.098 0.000
.cope3_t2 0.668 0.080 8.316 0.000
.cope4_t2 0.461 0.063 7.318 0.000
.cope5_t2 1.249 0.061 20.519 0.000
.cope6_t2 0.890 0.085 10.451 0.000
.cope7_t2 1.009 0.066 15.329 0.000
.cope8_t2 0.869 0.075 11.547 0.000
.cope9_t2 0.987 0.084 11.817 0.000
.rsvap1_t1 0.160 0.059 2.683 0.007
.rsvap2_t1 0.823 0.112 7.368 0.000
.rsvap3_t1 0.442 0.087 5.087 0.000
.rsvap4_t1 0.185 0.064 2.896 0.004
.rsvap5_t1 0.938 0.109 8.634 0.000
.rsvap1_t2 0.176 0.105 1.674 0.094
.rsvap2_t2 0.535 0.138 3.882 0.000
.rsvap3_t2 0.457 0.124 3.685 0.000
.rsvap4_t2 0.260 0.111 2.341 0.019
.rsvap5_t2 0.640 0.158 4.059 0.000
.attnic_t2 0.707 0.100 7.092 0.000
.knovap_t2 0.032 0.009 3.352 0.001
.rsk1_t2 0.410 0.046 8.996 0.000
.usevap1_t2 0.381 0.083 4.569 0.000
coping_t1 0.003 0.011 0.239 0.811
.coping_t2 0.246 0.069 3.567 0.000
Refusal_t1 0.701 0.102 6.854 0.000
.Refusal_t2 0.421 0.108 3.894 0.000Trying a reduced model where intermediary variables become outcomes
Vaping_Interm <- '
##Latent Variables##
coping_t1 =~ cope1_t1 + cope2_t1 + cope3_t1 + cope4_t1 + cope5_t1 +
cope6_t1 + cope7_t1 + cope8_t1 + cope9_t1
coping_t2 =~ cope1_t2 + cope2_t2 + cope3_t2 + cope4_t2 + cope5_t2 +
cope6_t2 + cope7_t2 + cope8_t2 + cope9_t2
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
##Regressions
coping_t2 ~ coping_t1 +rapd
Refusal_t2 ~ Refusal_t1 + rapd
knovap_t2 ~ knovap_t1 + rapd
rsk1_t2 ~ rsk1_t1 +rapd
attnic_t2 ~ attnic_t1 + rapd
'
Vaping_Interm_fit <- sem(Vaping_Interm, data = Student_Data_Full_No_NA, estimator = "mlr",
sampling.weights = "ipw",
mimic = "Mplus")
summary(Vaping_Interm_fit, fit.measures = TRUE)lavaan 0.6-19 ended normally after 226 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 111
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 2199.967 2057.910
Degrees of freedom 540 540
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.069
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 4386.030 3803.474
Degrees of freedom 589 589
P-value 0.000 0.000
Scaling correction factor 1.153
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.563 0.528
Tucker-Lewis Index (TLI) 0.523 0.485
Robust Comparative Fit Index (CFI) 0.570
Robust Tucker-Lewis Index (TLI) 0.531
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -12019.228 -12019.228
Scaling correction factor 1.522
for the MLR correction
Loglikelihood unrestricted model (H1) -10919.245 -10919.245
Scaling correction factor 1.146
for the MLR correction
Akaike (AIC) 24260.457 24260.457
Bayesian (BIC) 24672.681 24672.681
Sample-size adjusted Bayesian (SABIC) 24320.647 24320.647
Root Mean Square Error of Approximation:
RMSEA 0.101 0.096
90 Percent confidence interval - lower 0.096 0.092
90 Percent confidence interval - upper 0.105 0.101
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 1.000
Robust RMSEA 0.099
90 Percent confidence interval - lower 0.094
90 Percent confidence interval - upper 0.104
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 1.000
Standardized Root Mean Square Residual:
SRMR 0.105 0.105
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|)
coping_t1 =~
cope1_t1 1.000
cope2_t1 -12.590 27.822 -0.453 0.651
cope3_t1 5.312 8.796 0.604 0.546
cope4_t1 0.274 2.499 0.110 0.913
cope5_t1 -5.567 13.255 -0.420 0.674
cope6_t1 8.293 14.785 0.561 0.575
cope7_t1 -7.911 16.774 -0.472 0.637
cope8_t1 3.425 5.832 0.587 0.557
cope9_t1 -2.100 4.786 -0.439 0.661
coping_t2 =~
cope1_t2 1.000
cope2_t2 0.429 0.185 2.321 0.020
cope3_t2 1.432 0.241 5.947 0.000
cope4_t2 1.483 0.203 7.296 0.000
cope5_t2 0.241 0.171 1.415 0.157
cope6_t2 1.218 0.219 5.572 0.000
cope7_t2 0.559 0.179 3.126 0.002
cope8_t2 0.876 0.187 4.683 0.000
cope9_t2 0.938 0.184 5.099 0.000
Refusal_t1 =~
rsvap1_t1 1.000
rsvap2_t1 0.808 0.119 6.789 0.000
rsvap3_t1 0.952 0.106 9.007 0.000
rsvap4_t1 0.956 0.038 24.841 0.000
rsvap5_t1 0.743 0.123 6.035 0.000
Refusal_t2 =~
rsvap1_t2 1.000
rsvap2_t2 1.031 0.231 4.452 0.000
rsvap3_t2 0.983 0.232 4.236 0.000
rsvap4_t2 1.040 0.055 18.998 0.000
rsvap5_t2 0.981 0.262 3.743 0.000
Regressions:
Estimate Std.Err z-value P(>|z|)
coping_t2 ~
coping_t1 1.088 1.884 0.577 0.564
rapd 0.008 0.191 0.044 0.965
Refusal_t2 ~
Refusal_t1 0.361 0.074 4.892 0.000
rapd 0.466 0.278 1.675 0.094
knovap_t2 ~
knovap_t1 0.091 0.116 0.787 0.431
rapd 0.046 0.093 0.489 0.625
rsk1_t2 ~
rsk1_t1 0.229 0.067 3.410 0.001
rapd 0.368 0.271 1.359 0.174
attnic_t2 ~
attnic_t1 0.376 0.083 4.546 0.000
rapd 0.115 0.293 0.394 0.694
Covariances:
Estimate Std.Err z-value P(>|z|)
coping_t1 ~~
Refusal_t1 -0.003 0.008 -0.370 0.712
.coping_t2 ~~
.Refusal_t2 0.130 0.040 3.245 0.001
.knovap_t2 0.015 0.009 1.676 0.094
.rsk1_t2 0.080 0.033 2.434 0.015
.attnic_t2 0.093 0.043 2.180 0.029
.Refusal_t2 ~~
.knovap_t2 0.018 0.015 1.233 0.217
.rsk1_t2 0.078 0.040 1.945 0.052
.attnic_t2 0.140 0.047 2.964 0.003
.knovap_t2 ~~
.rsk1_t2 0.023 0.015 1.554 0.120
.attnic_t2 0.009 0.009 1.028 0.304
.rsk1_t2 ~~
.attnic_t2 0.187 0.049 3.807 0.000
Intercepts:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 2.502 0.063 39.527 0.000
.cope2_t1 2.469 0.065 37.806 0.000
.cope3_t1 2.822 0.062 45.808 0.000
.cope4_t1 2.769 0.067 41.444 0.000
.cope5_t1 1.990 0.059 33.869 0.000
.cope6_t1 2.917 0.063 46.530 0.000
.cope7_t1 2.531 0.062 40.682 0.000
.cope8_t1 2.376 0.066 35.772 0.000
.cope9_t1 2.667 0.062 42.985 0.000
.cope1_t2 2.787 0.190 14.659 0.000
.cope2_t2 2.465 0.105 23.398 0.000
.cope3_t2 2.592 0.270 9.613 0.000
.cope4_t2 2.955 0.282 10.485 0.000
.cope5_t2 2.252 0.080 28.056 0.000
.cope6_t2 2.884 0.235 12.275 0.000
.cope7_t2 2.415 0.119 20.325 0.000
.cope8_t2 2.257 0.173 13.072 0.000
.cope9_t2 2.629 0.183 14.375 0.000
.rsvap1_t1 3.442 0.053 64.592 0.000
.rsvap2_t1 2.974 0.065 45.872 0.000
.rsvap3_t1 3.122 0.059 52.517 0.000
.rsvap4_t1 3.439 0.052 65.820 0.000
.rsvap5_t1 2.954 0.066 44.786 0.000
.rsvap1_t2 2.983 0.280 10.644 0.000
.rsvap2_t2 2.683 0.281 9.556 0.000
.rsvap3_t2 2.826 0.276 10.221 0.000
.rsvap4_t2 2.959 0.286 10.347 0.000
.rsvap5_t2 2.714 0.277 9.803 0.000
.knovap_t2 0.834 0.125 6.681 0.000
.rsk1_t2 1.542 0.320 4.821 0.000
.attnic_t2 2.543 0.446 5.699 0.000
Variances:
Estimate Std.Err z-value P(>|z|)
.cope1_t1 1.210 0.059 20.488 0.000
.cope2_t1 0.735 0.344 2.138 0.033
.cope3_t1 1.051 0.151 6.963 0.000
.cope4_t1 1.352 0.063 21.320 0.000
.cope5_t1 0.937 0.134 6.971 0.000
.cope6_t1 0.949 0.222 4.285 0.000
.cope7_t1 0.953 0.116 8.230 0.000
.cope8_t1 1.296 0.102 12.651 0.000
.cope9_t1 1.151 0.061 18.889 0.000
.cope1_t2 0.709 0.072 9.819 0.000
.cope2_t2 1.245 0.067 18.697 0.000
.cope3_t2 0.731 0.086 8.500 0.000
.cope4_t2 0.387 0.070 5.546 0.000
.cope5_t2 1.251 0.061 20.488 0.000
.cope6_t2 0.901 0.084 10.713 0.000
.cope7_t2 1.009 0.066 15.324 0.000
.cope8_t2 0.905 0.080 11.260 0.000
.cope9_t2 1.019 0.083 12.219 0.000
.rsvap1_t1 0.162 0.065 2.489 0.013
.rsvap2_t1 0.817 0.117 6.998 0.000
.rsvap3_t1 0.438 0.092 4.782 0.000
.rsvap4_t1 0.189 0.069 2.746 0.006
.rsvap5_t1 0.932 0.115 8.122 0.000
.rsvap1_t2 0.193 0.115 1.682 0.093
.rsvap2_t2 0.520 0.135 3.840 0.000
.rsvap3_t2 0.433 0.125 3.457 0.001
.rsvap4_t2 0.280 0.125 2.239 0.025
.rsvap5_t2 0.607 0.163 3.737 0.000
.knovap_t2 0.032 0.009 3.350 0.001
.rsk1_t2 0.411 0.046 8.933 0.000
.attnic_t2 0.712 0.100 7.092 0.000
coping_t1 0.004 0.014 0.248 0.804
.coping_t2 0.253 0.068 3.696 0.000
Refusal_t1 0.699 0.106 6.620 0.000
.Refusal_t2 0.413 0.113 3.648 0.000Vaping Outcome Only
Vaping_Model_Outcome <- '
##Latent Variables##
coping_t1 =~ cope1_t1 + cope2_t1 + cope3_t1 + cope4_t1 + cope5_t1 +
cope6_t1 + cope7_t1 + cope8_t1 + cope9_t1
coping_t2 =~ cope1_t2 + cope2_t2 + cope3_t2 + cope4_t2 + cope5_t2 +
cope6_t2 + cope7_t2 + cope8_t2 + cope9_t2
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
usevap1_t2 ~ usevap1_t1 +coping_t2 + Refusal_t2 + knovap_t2 + rsk1_t2 +
attnic_t2 + rapd
'
Vaping_Model_Outcome_Fit <- sem(Vaping_Model_Outcome, data = Student_Data_Full_No_NA, estimator = "mlr",
sampling.weights = "ipw",
mimic = "Mplus")
summary(Vaping_Model_Outcome_Fit, fit.measures = TRUE, standardized = TRUE)lavaan 0.6-19 ended normally after 266 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 99
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 2164.673 2032.546
Degrees of freedom 510 510
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.065
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 4218.349 3685.693
Degrees of freedom 551 551
P-value 0.000 0.000
Scaling correction factor 1.145
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.549 0.514
Tucker-Lewis Index (TLI) 0.513 0.475
Robust Comparative Fit Index (CFI) 0.557
Robust Tucker-Lewis Index (TLI) 0.522
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -11766.000 -11766.000
Scaling correction factor 1.438
for the MLR correction
Loglikelihood unrestricted model (H1) -10683.664 -10683.664
Scaling correction factor 1.126
for the MLR correction
Akaike (AIC) 23730.000 23730.000
Bayesian (BIC) 24097.659 24097.659
Sample-size adjusted Bayesian (SABIC) 23783.683 23783.683
Root Mean Square Error of Approximation:
RMSEA 0.103 0.099
90 Percent confidence interval - lower 0.099 0.095
90 Percent confidence interval - upper 0.108 0.104
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 1.000
Robust RMSEA 0.102
90 Percent confidence interval - lower 0.097
90 Percent confidence interval - upper 0.106
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 1.000
Standardized Root Mean Square Residual:
SRMR 0.106 0.106
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
coping_t1 =~
cope1_t1 1.000 0.060 0.054
cope2_t1 -12.536 36.593 -0.343 0.732 -0.750 -0.660
cope3_t1 5.361 9.437 0.568 0.570 0.321 0.299
cope4_t1 -0.084 3.915 -0.022 0.983 -0.005 -0.004
cope5_t1 -5.112 16.953 -0.302 0.763 -0.306 -0.299
cope6_t1 8.647 16.925 0.511 0.609 0.517 0.474
cope7_t1 -7.303 20.092 -0.363 0.716 -0.437 -0.403
cope8_t1 4.154 7.106 0.585 0.559 0.249 0.215
cope9_t1 -1.489 4.549 -0.327 0.743 -0.089 -0.083
coping_t2 =~
cope1_t2 1.000 0.497 0.507
cope2_t2 0.429 0.194 2.216 0.027 0.213 0.188
cope3_t2 1.480 0.244 6.069 0.000 0.736 0.658
cope4_t2 1.475 0.204 7.243 0.000 0.733 0.755
cope5_t2 0.264 0.170 1.554 0.120 0.131 0.117
cope6_t2 1.248 0.228 5.472 0.000 0.620 0.549
cope7_t2 0.561 0.178 3.154 0.002 0.279 0.268
cope8_t2 0.883 0.184 4.793 0.000 0.439 0.419
cope9_t2 0.960 0.181 5.289 0.000 0.477 0.428
Refusal_t1 =~
rsvap1_t1 1.000 0.836 0.901
rsvap2_t1 0.810 0.118 6.855 0.000 0.677 0.600
rsvap3_t1 0.954 0.105 9.107 0.000 0.797 0.770
rsvap4_t1 0.955 0.038 24.904 0.000 0.798 0.878
rsvap5_t1 0.744 0.122 6.083 0.000 0.622 0.542
Refusal_t2 =~
rsvap1_t2 1.000 0.749 0.870
rsvap2_t2 1.005 0.200 5.038 0.000 0.753 0.717
rsvap3_t2 0.953 0.201 4.734 0.000 0.714 0.728
rsvap4_t2 1.042 0.054 19.310 0.000 0.780 0.836
rsvap5_t2 0.944 0.226 4.176 0.000 0.707 0.664
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
usevap1_t2 ~
usevap1_t1 -0.036 0.026 -1.382 0.167 -0.036 -0.062
coping_t2 0.172 0.107 1.598 0.110 0.085 0.130
Refusal_t2 -0.276 0.083 -3.344 0.001 -0.207 -0.316
knovap_t2 -0.216 0.289 -0.746 0.456 -0.216 -0.059
rsk1_t2 -0.064 0.066 -0.967 0.333 -0.064 -0.066
attnic_t2 -0.035 0.055 -0.623 0.533 -0.035 -0.049
rapd -0.340 0.280 -1.215 0.224 -0.340 -0.097
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
coping_t1 ~~
coping_t2 0.001 0.009 0.108 0.914 0.031 0.031
Refusal_t1 -0.002 0.007 -0.325 0.745 -0.047 -0.047
Refusal_t2 -0.010 0.027 -0.363 0.716 -0.222 -0.222
coping_t2 ~~
Refusal_t1 0.034 0.034 0.998 0.318 0.082 0.082
Refusal_t2 0.135 0.042 3.225 0.001 0.362 0.362
Refusal_t1 ~~
Refusal_t2 0.311 0.062 5.007 0.000 0.496 0.496
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.cope1_t1 2.502 0.063 39.527 0.000 2.502 2.271
.cope2_t1 2.469 0.065 37.806 0.000 2.469 2.172
.cope3_t1 2.822 0.062 45.808 0.000 2.822 2.632
.cope4_t1 2.769 0.067 41.444 0.000 2.769 2.381
.cope5_t1 1.990 0.059 33.869 0.000 1.990 1.946
.cope6_t1 2.917 0.063 46.530 0.000 2.917 2.673
.cope7_t1 2.531 0.062 40.682 0.000 2.531 2.337
.cope8_t1 2.376 0.066 35.772 0.000 2.376 2.055
.cope9_t1 2.667 0.062 42.985 0.000 2.667 2.469
.cope1_t2 2.795 0.056 49.625 0.000 2.795 2.851
.cope2_t2 2.469 0.065 37.806 0.000 2.469 2.172
.cope3_t2 2.604 0.064 40.556 0.000 2.604 2.330
.cope4_t2 2.967 0.056 53.190 0.000 2.967 3.056
.cope5_t2 2.254 0.065 34.880 0.000 2.254 2.004
.cope6_t2 2.894 0.065 44.602 0.000 2.894 2.562
.cope7_t2 2.419 0.060 40.364 0.000 2.419 2.319
.cope8_t2 2.264 0.060 37.599 0.000 2.264 2.160
.cope9_t2 2.637 0.064 41.202 0.000 2.637 2.367
.rsvap1_t1 3.442 0.053 64.592 0.000 3.442 3.711
.rsvap2_t1 2.974 0.065 45.872 0.000 2.974 2.635
.rsvap3_t1 3.122 0.059 52.517 0.000 3.122 3.017
.rsvap4_t1 3.439 0.052 65.820 0.000 3.439 3.781
.rsvap5_t1 2.954 0.066 44.786 0.000 2.954 2.573
.rsvap1_t2 3.432 0.049 69.432 0.000 3.432 3.989
.rsvap2_t2 3.145 0.060 52.176 0.000 3.145 2.997
.rsvap3_t2 3.267 0.056 58.000 0.000 3.267 3.332
.rsvap4_t2 3.426 0.054 63.875 0.000 3.426 3.670
.rsvap5_t2 3.155 0.061 51.566 0.000 3.155 2.962
.usevap1_t2 1.049 0.475 2.210 0.027 1.049 1.602
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.cope1_t1 1.210 0.060 20.044 0.000 1.210 0.997
.cope2_t1 0.729 0.627 1.163 0.245 0.729 0.565
.cope3_t1 1.047 0.225 4.660 0.000 1.047 0.911
.cope4_t1 1.353 0.063 21.397 0.000 1.353 1.000
.cope5_t1 0.953 0.198 4.805 0.000 0.953 0.911
.cope6_t1 0.924 0.401 2.301 0.021 0.924 0.775
.cope7_t1 0.982 0.156 6.277 0.000 0.982 0.837
.cope8_t1 1.275 0.184 6.948 0.000 1.275 0.954
.cope9_t1 1.158 0.060 19.377 0.000 1.158 0.993
.cope1_t2 0.714 0.072 9.944 0.000 0.714 0.743
.cope2_t2 1.246 0.067 18.537 0.000 1.246 0.965
.cope3_t2 0.708 0.082 8.616 0.000 0.708 0.567
.cope4_t2 0.405 0.071 5.722 0.000 0.405 0.430
.cope5_t2 1.248 0.061 20.479 0.000 1.248 0.986
.cope6_t2 0.891 0.087 10.199 0.000 0.891 0.698
.cope7_t2 1.010 0.065 15.488 0.000 1.010 0.928
.cope8_t2 0.906 0.078 11.602 0.000 0.906 0.825
.cope9_t2 1.013 0.082 12.335 0.000 1.013 0.817
.rsvap1_t1 0.162 0.065 2.502 0.012 0.162 0.189
.rsvap2_t1 0.815 0.116 7.024 0.000 0.815 0.640
.rsvap3_t1 0.436 0.090 4.834 0.000 0.436 0.407
.rsvap4_t1 0.190 0.068 2.779 0.005 0.190 0.230
.rsvap5_t1 0.931 0.114 8.180 0.000 0.931 0.707
.rsvap1_t2 0.180 0.098 1.833 0.067 0.180 0.243
.rsvap2_t2 0.535 0.126 4.246 0.000 0.535 0.485
.rsvap3_t2 0.452 0.115 3.935 0.000 0.452 0.470
.rsvap4_t2 0.263 0.104 2.517 0.012 0.263 0.301
.rsvap5_t2 0.635 0.148 4.279 0.000 0.635 0.560
.usevap1_t2 0.380 0.083 4.587 0.000 0.380 0.885
coping_t1 0.004 0.018 0.203 0.839 1.000 1.000
coping_t2 0.247 0.068 3.632 0.000 1.000 1.000
Refusal_t1 0.698 0.105 6.628 0.000 1.000 1.000
Refusal_t2 0.561 0.125 4.470 0.000 1.000 1.000Reduced Models:
Vaping_Model_Intermedite <- '
##Latent Variables##
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
rsvap1_t1 ~~ rsvap4_t1
rsvap1_t1 ~~ rsvap5_t1
rsvap2_t1 ~~ rsvap5_t1
rsvap1_t2 ~~ rsvap4_t2
usevap1_t2 ~ usevap1_t1+ Refusal_t2
Refusal_t2 ~ Refusal_t1 + rapd
knovap_t2 ~ knovap_t1 +rapd
rsk1_t2 ~ rsk1_t1 + rapd
attnic_t2 ~ attnic_t1 + rapd
'
Vaping_Model_Intermedite_Fit <- sem(Vaping_Model_Intermedite, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",
mimic = "Mplus")
summary(Vaping_Model_Intermedite_Fit, fit.measures = TRUE, standardized = TRUE)lavaan 0.6-19 ended normally after 93 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 58
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 420.001 344.163
Degrees of freedom 131 131
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.220
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2437.657 1730.634
Degrees of freedom 161 161
P-value 0.000 0.000
Scaling correction factor 1.409
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.873 0.864
Tucker-Lewis Index (TLI) 0.844 0.833
Robust Comparative Fit Index (CFI) 0.887
Robust Tucker-Lewis Index (TLI) 0.861
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -4220.708 -4220.708
Scaling correction factor 2.021
for the MLR correction
Loglikelihood unrestricted model (H1) -4010.707 -4010.707
Scaling correction factor 1.466
for the MLR correction
Akaike (AIC) 8557.415 8557.415
Bayesian (BIC) 8772.812 8772.812
Sample-size adjusted Bayesian (SABIC) 8588.866 8588.866
Root Mean Square Error of Approximation:
RMSEA 0.085 0.073
90 Percent confidence interval - lower 0.076 0.065
90 Percent confidence interval - upper 0.095 0.082
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.836 0.101
Robust RMSEA 0.080
90 Percent confidence interval - lower 0.069
90 Percent confidence interval - upper 0.090
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.488
Standardized Root Mean Square Residual:
SRMR 0.113 0.113
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
Refusal_t1 =~
rsvap1_t1 1.000 0.669 0.723
rsvap2_t1 1.126 0.129 8.707 0.000 0.753 0.667
rsvap3_t1 1.416 0.143 9.911 0.000 0.947 0.915
rsvap4_t1 0.919 0.057 16.227 0.000 0.614 0.676
rsvap5_t1 1.143 0.139 8.220 0.000 0.764 0.665
Refusal_t2 =~
rsvap1_t2 1.000 0.585 0.683
rsvap2_t2 1.451 0.167 8.679 0.000 0.849 0.814
rsvap3_t2 1.359 0.161 8.462 0.000 0.795 0.816
rsvap4_t2 0.998 0.083 11.982 0.000 0.584 0.628
rsvap5_t2 1.438 0.174 8.281 0.000 0.841 0.795
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
usevap1_t2 ~
usevap1_t1 -0.030 0.028 -1.069 0.285 -0.030 -0.051
Refusal_t2 -0.266 0.092 -2.885 0.004 -0.155 -0.235
Refusal_t2 ~
Refusal_t1 0.459 0.084 5.476 0.000 0.525 0.525
rapd 0.268 0.198 1.357 0.175 0.459 0.086
knovap_t2 ~
knovap_t1 0.076 0.114 0.669 0.504 0.076 0.072
rapd 0.038 0.084 0.445 0.656 0.038 0.039
rsk1_t2 ~
rsk1_t1 0.222 0.067 3.331 0.001 0.222 0.220
rapd 0.333 0.269 1.239 0.215 0.333 0.094
attnic_t2 ~
attnic_t1 0.389 0.082 4.722 0.000 0.389 0.366
rapd 0.066 0.274 0.242 0.809 0.066 0.014
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 ~~
.rsvap4_t1 0.292 0.056 5.227 0.000 0.292 0.682
.rsvap5_t1 -0.054 0.033 -1.624 0.104 -0.054 -0.098
.rsvap2_t1 ~~
.rsvap5_t1 0.202 0.069 2.927 0.003 0.202 0.280
.rsvap1_t2 ~~
.rsvap4_t2 0.309 0.051 6.081 0.000 0.309 0.683
.usevap1_t2 ~~
.knovap_t2 -0.010 0.011 -0.883 0.377 -0.010 -0.088
.rsk1_t2 -0.037 0.031 -1.189 0.234 -0.037 -0.090
.attnic_t2 -0.036 0.033 -1.110 0.267 -0.036 -0.067
.knovap_t2 ~~
.rsk1_t2 0.023 0.015 1.554 0.120 0.023 0.204
.attnic_t2 0.009 0.009 1.046 0.296 0.009 0.062
.rsk1_t2 ~~
.attnic_t2 0.187 0.049 3.774 0.000 0.187 0.345
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 3.442 0.053 64.592 0.000 3.442 3.721
.rsvap2_t1 2.974 0.065 45.872 0.000 2.974 2.635
.rsvap3_t1 3.122 0.059 52.516 0.000 3.122 3.017
.rsvap4_t1 3.439 0.052 65.820 0.000 3.439 3.781
.rsvap5_t1 2.954 0.066 44.786 0.000 2.954 2.569
.rsvap1_t2 3.174 0.205 15.502 0.000 3.174 3.705
.rsvap2_t2 2.770 0.267 10.369 0.000 2.770 2.657
.rsvap3_t2 2.916 0.255 11.451 0.000 2.916 2.993
.rsvap4_t2 3.168 0.203 15.643 0.000 3.168 3.406
.rsvap5_t2 2.783 0.266 10.451 0.000 2.783 2.629
.usevap1_t2 0.268 0.084 3.211 0.001 0.268 0.406
.knovap_t2 0.857 0.116 7.359 0.000 0.857 4.798
.rsk1_t2 1.593 0.312 5.111 0.000 1.593 2.402
.attnic_t2 2.532 0.433 5.848 0.000 2.532 2.792
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 0.409 0.057 7.130 0.000 0.409 0.477
.rsvap2_t1 0.707 0.093 7.638 0.000 0.707 0.555
.rsvap3_t1 0.174 0.057 3.039 0.002 0.174 0.162
.rsvap4_t1 0.450 0.055 8.234 0.000 0.450 0.544
.rsvap5_t1 0.738 0.091 8.087 0.000 0.738 0.558
.rsvap1_t2 0.392 0.051 7.718 0.000 0.392 0.534
.rsvap2_t2 0.367 0.060 6.151 0.000 0.367 0.338
.rsvap3_t2 0.317 0.053 5.952 0.000 0.317 0.334
.rsvap4_t2 0.524 0.065 8.069 0.000 0.524 0.606
.rsvap5_t2 0.413 0.068 6.105 0.000 0.413 0.369
.usevap1_t2 0.412 0.089 4.613 0.000 0.412 0.942
.knovap_t2 0.032 0.009 3.351 0.001 0.032 0.992
.rsk1_t2 0.412 0.046 8.913 0.000 0.412 0.937
.attnic_t2 0.710 0.100 7.087 0.000 0.710 0.864
Refusal_t1 0.447 0.093 4.823 0.000 1.000 1.000
.Refusal_t2 0.245 0.060 4.076 0.000 0.717 0.717modificationindices(Vaping_Model_Intermedite_Fit) lhs op rhs mi epc sepc.lv sepc.all sepc.nox
47 usevap1_t1 ~~ usevap1_t1 0.000 0.000 0.000 0.000 0.000
48 usevap1_t1 ~~ rapd 0.000 0.000 0.000 NA 0.000
49 usevap1_t1 ~~ knovap_t1 0.000 0.000 0.000 NA 0.000
50 usevap1_t1 ~~ rsk1_t1 0.000 0.000 0.000 NA 0.000
51 usevap1_t1 ~~ attnic_t1 0.000 0.000 0.000 NA 0.000
52 rapd ~~ rapd 0.000 0.000 0.000 0.000 0.000
53 rapd ~~ knovap_t1 0.000 0.000 0.000 NA 0.000
54 rapd ~~ rsk1_t1 0.000 0.000 0.000 NA 0.000
55 rapd ~~ attnic_t1 0.000 0.000 0.000 NA 0.000
56 knovap_t1 ~~ knovap_t1 0.000 0.000 0.000 0.000 0.000
57 knovap_t1 ~~ rsk1_t1 0.000 0.000 0.000 NA 0.000
58 knovap_t1 ~~ attnic_t1 0.000 0.000 0.000 NA 0.000
59 rsk1_t1 ~~ rsk1_t1 0.000 0.000 0.000 0.000 0.000
60 rsk1_t1 ~~ attnic_t1 0.000 0.000 0.000 NA 0.000
61 attnic_t1 ~~ attnic_t1 0.000 0.000 0.000 0.000 0.000
83 Refusal_t1 =~ rsvap1_t2 0.511 -0.038 -0.025 -0.029 -0.029
84 Refusal_t1 =~ rsvap2_t2 0.719 -0.071 -0.047 -0.045 -0.045
85 Refusal_t1 =~ rsvap3_t2 0.160 0.031 0.021 0.021 0.021
86 Refusal_t1 =~ rsvap4_t2 0.582 0.046 0.031 0.033 0.033
87 Refusal_t1 =~ rsvap5_t2 0.003 -0.004 -0.003 -0.003 -0.003
88 Refusal_t2 =~ rsvap1_t1 0.931 -0.061 -0.036 -0.039 -0.039
89 Refusal_t2 =~ rsvap2_t1 0.883 0.103 0.060 0.053 0.053
90 Refusal_t2 =~ rsvap3_t1 0.419 -0.072 -0.042 -0.041 -0.041
91 Refusal_t2 =~ rsvap4_t1 0.018 0.009 0.005 0.005 0.005
92 Refusal_t2 =~ rsvap5_t1 2.795 0.189 0.111 0.096 0.096
93 rsvap1_t1 ~~ rsvap2_t1 2.034 0.038 0.038 0.070 0.070
94 rsvap1_t1 ~~ rsvap3_t1 0.112 -0.010 -0.010 -0.037 -0.037
95 rsvap1_t1 ~~ rsvap1_t2 0.980 0.013 0.013 0.031 0.031
96 rsvap1_t1 ~~ rsvap2_t2 0.001 -0.001 -0.001 -0.002 -0.002
97 rsvap1_t1 ~~ rsvap3_t2 0.548 -0.013 -0.013 -0.037 -0.037
98 rsvap1_t1 ~~ rsvap4_t2 0.537 -0.011 -0.011 -0.023 -0.023
99 rsvap1_t1 ~~ rsvap5_t2 0.822 -0.018 -0.018 -0.044 -0.044
100 rsvap1_t1 ~~ usevap1_t2 0.003 0.001 0.001 0.002 0.002
101 rsvap1_t1 ~~ knovap_t2 0.003 0.000 0.000 -0.002 -0.002
102 rsvap1_t1 ~~ rsk1_t2 0.104 0.005 0.005 0.013 0.013
103 rsvap1_t1 ~~ attnic_t2 0.912 -0.021 -0.021 -0.038 -0.038
104 rsvap2_t1 ~~ rsvap3_t1 1.948 -0.071 -0.071 -0.203 -0.203
105 rsvap2_t1 ~~ rsvap4_t1 0.671 -0.020 -0.020 -0.036 -0.036
106 rsvap2_t1 ~~ rsvap1_t2 0.127 0.008 0.008 0.015 0.015
107 rsvap2_t1 ~~ rsvap2_t2 9.950 0.105 0.105 0.205 0.205
108 rsvap2_t1 ~~ rsvap3_t2 5.623 -0.073 -0.073 -0.155 -0.155
109 rsvap2_t1 ~~ rsvap4_t2 0.099 0.008 0.008 0.013 0.013
110 rsvap2_t1 ~~ rsvap5_t2 0.240 -0.017 -0.017 -0.031 -0.031
111 rsvap2_t1 ~~ usevap1_t2 0.971 0.030 0.030 0.055 0.055
112 rsvap2_t1 ~~ knovap_t2 0.014 0.001 0.001 0.007 0.007
113 rsvap2_t1 ~~ rsk1_t2 0.001 0.001 0.001 0.002 0.002
114 rsvap2_t1 ~~ attnic_t2 0.035 0.007 0.007 0.010 0.010
115 rsvap3_t1 ~~ rsvap4_t1 1.971 0.038 0.038 0.138 0.138
116 rsvap3_t1 ~~ rsvap5_t1 0.251 0.027 0.027 0.075 0.075
117 rsvap3_t1 ~~ rsvap1_t2 3.539 -0.032 -0.032 -0.123 -0.123
118 rsvap3_t1 ~~ rsvap2_t2 0.677 -0.021 -0.021 -0.085 -0.085
119 rsvap3_t1 ~~ rsvap3_t2 3.397 0.045 0.045 0.191 0.191
120 rsvap3_t1 ~~ rsvap4_t2 0.088 -0.006 -0.006 -0.019 -0.019
121 rsvap3_t1 ~~ rsvap5_t2 0.098 0.008 0.008 0.032 0.032
122 rsvap3_t1 ~~ usevap1_t2 2.383 -0.036 -0.036 -0.135 -0.135
123 rsvap3_t1 ~~ knovap_t2 0.070 -0.002 -0.002 -0.023 -0.023
124 rsvap3_t1 ~~ rsk1_t2 0.040 -0.004 -0.004 -0.016 -0.016
125 rsvap3_t1 ~~ attnic_t2 0.735 -0.025 -0.025 -0.071 -0.071
126 rsvap4_t1 ~~ rsvap5_t1 3.145 -0.068 -0.068 -0.118 -0.118
127 rsvap4_t1 ~~ rsvap1_t2 0.507 0.009 0.009 0.022 0.022
128 rsvap4_t1 ~~ rsvap2_t2 5.948 -0.048 -0.048 -0.118 -0.118
129 rsvap4_t1 ~~ rsvap3_t2 0.616 0.014 0.014 0.038 0.038
130 rsvap4_t1 ~~ rsvap4_t2 9.091 0.045 0.045 0.093 0.093
131 rsvap4_t1 ~~ rsvap5_t2 2.358 -0.031 -0.031 -0.073 -0.073
132 rsvap4_t1 ~~ usevap1_t2 0.776 -0.016 -0.016 -0.037 -0.037
133 rsvap4_t1 ~~ knovap_t2 0.241 0.002 0.002 0.020 0.020
134 rsvap4_t1 ~~ rsk1_t2 0.227 0.008 0.008 0.018 0.018
135 rsvap4_t1 ~~ attnic_t2 3.317 0.040 0.040 0.072 0.072
136 rsvap5_t1 ~~ rsvap1_t2 0.242 -0.011 -0.011 -0.021 -0.021
137 rsvap5_t1 ~~ rsvap2_t2 0.369 0.021 0.021 0.040 0.040
138 rsvap5_t1 ~~ rsvap3_t2 0.028 -0.005 -0.005 -0.011 -0.011
139 rsvap5_t1 ~~ rsvap4_t2 4.321 -0.053 -0.053 -0.086 -0.086
140 rsvap5_t1 ~~ rsvap5_t2 12.342 0.124 0.124 0.224 0.224
141 rsvap5_t1 ~~ usevap1_t2 0.222 -0.015 -0.015 -0.026 -0.026
142 rsvap5_t1 ~~ knovap_t2 0.281 0.004 0.004 0.029 0.029
143 rsvap5_t1 ~~ rsk1_t2 0.655 -0.023 -0.023 -0.042 -0.042
144 rsvap5_t1 ~~ attnic_t2 0.075 -0.010 -0.010 -0.014 -0.014
145 rsvap1_t2 ~~ rsvap2_t2 1.653 0.026 0.026 0.069 0.069
146 rsvap1_t2 ~~ rsvap3_t2 5.572 -0.045 -0.045 -0.127 -0.127
147 rsvap1_t2 ~~ rsvap5_t2 0.863 0.019 0.019 0.048 0.048
148 rsvap1_t2 ~~ usevap1_t2 2.123 -0.025 -0.025 -0.062 -0.062
149 rsvap1_t2 ~~ knovap_t2 0.085 -0.001 -0.001 -0.012 -0.012
150 rsvap1_t2 ~~ rsk1_t2 3.829 0.031 0.031 0.077 0.077
151 rsvap1_t2 ~~ attnic_t2 0.221 -0.010 -0.010 -0.019 -0.019
152 rsvap2_t2 ~~ rsvap3_t2 2.894 -0.066 -0.066 -0.192 -0.192
153 rsvap2_t2 ~~ rsvap4_t2 0.485 -0.016 -0.016 -0.036 -0.036
154 rsvap2_t2 ~~ rsvap5_t2 3.218 0.073 0.073 0.188 0.188
155 rsvap2_t2 ~~ usevap1_t2 1.878 0.036 0.036 0.093 0.093
156 rsvap2_t2 ~~ knovap_t2 0.095 -0.002 -0.002 -0.020 -0.020
157 rsvap2_t2 ~~ rsk1_t2 2.781 -0.039 -0.039 -0.102 -0.102
158 rsvap2_t2 ~~ attnic_t2 1.561 -0.040 -0.040 -0.078 -0.078
159 rsvap3_t2 ~~ rsvap4_t2 8.833 0.063 0.063 0.153 0.153
160 rsvap3_t2 ~~ rsvap5_t2 1.283 0.043 0.043 0.120 0.120
161 rsvap3_t2 ~~ usevap1_t2 0.085 -0.007 -0.007 -0.020 -0.020
162 rsvap3_t2 ~~ knovap_t2 0.133 0.002 0.002 0.024 0.024
163 rsvap3_t2 ~~ rsk1_t2 2.035 0.031 0.031 0.087 0.087
164 rsvap3_t2 ~~ attnic_t2 6.993 0.078 0.078 0.165 0.165
165 rsvap4_t2 ~~ rsvap5_t2 8.016 -0.066 -0.066 -0.141 -0.141
166 rsvap4_t2 ~~ usevap1_t2 1.035 -0.020 -0.020 -0.043 -0.043
167 rsvap4_t2 ~~ knovap_t2 3.655 0.010 0.010 0.079 0.079
168 rsvap4_t2 ~~ rsk1_t2 1.010 -0.018 -0.018 -0.039 -0.039
169 rsvap4_t2 ~~ attnic_t2 2.466 0.038 0.038 0.062 0.062
170 rsvap5_t2 ~~ usevap1_t2 8.871 0.081 0.081 0.197 0.197
171 rsvap5_t2 ~~ knovap_t2 0.221 -0.003 -0.003 -0.030 -0.030
172 rsvap5_t2 ~~ rsk1_t2 0.002 0.001 0.001 0.002 0.002
173 rsvap5_t2 ~~ attnic_t2 0.242 0.016 0.016 0.030 0.030
175 usevap1_t2 ~ knovap_t2 0.698 -1.966 -1.966 -0.531 -0.531
176 usevap1_t2 ~ rsk1_t2 5.820 -0.534 -0.534 -0.536 -0.536
177 usevap1_t2 ~ attnic_t2 4.585 -0.237 -0.237 -0.325 -0.325
178 usevap1_t2 ~ Refusal_t1 6.589 -0.184 -0.123 -0.187 -0.187
179 usevap1_t2 ~ rapd 4.957 -0.447 -0.447 -0.126 -0.676
180 usevap1_t2 ~ knovap_t1 0.031 0.038 0.038 0.010 0.058
181 usevap1_t2 ~ rsk1_t1 3.344 -0.103 -0.103 -0.102 -0.156
182 usevap1_t2 ~ attnic_t1 4.302 -0.090 -0.090 -0.116 -0.136
183 Refusal_t2 ~ usevap1_t2 5.951 0.222 0.380 0.251 0.251
184 Refusal_t2 ~ knovap_t2 1.784 0.239 0.408 0.073 0.073
185 Refusal_t2 ~ rsk1_t2 7.462 0.132 0.226 0.150 0.150
186 Refusal_t2 ~ attnic_t2 18.387 0.151 0.259 0.235 0.235
187 Refusal_t2 ~ usevap1_t1 9.278 -0.086 -0.147 -0.168 -0.147
188 Refusal_t2 ~ knovap_t1 7.544 -0.523 -0.895 -0.152 -0.895
189 Refusal_t2 ~ rsk1_t1 2.430 0.077 0.131 0.086 0.131
190 Refusal_t2 ~ attnic_t1 4.014 0.076 0.130 0.111 0.130
191 knovap_t2 ~ usevap1_t2 3.226 -0.121 -0.121 -0.448 -0.448
192 knovap_t2 ~ Refusal_t2 3.110 0.032 0.019 0.106 0.106
193 knovap_t2 ~ rsk1_t2 0.186 0.031 0.031 0.114 0.114
194 knovap_t2 ~ attnic_t2 2.439 -0.048 -0.048 -0.243 -0.243
195 knovap_t2 ~ usevap1_t1 0.119 0.003 0.003 0.020 0.017
196 knovap_t2 ~ Refusal_t1 2.190 0.023 0.016 0.088 0.088
197 knovap_t2 ~ rsk1_t1 0.186 0.007 0.007 0.025 0.038
198 knovap_t2 ~ attnic_t1 2.439 -0.019 -0.019 -0.089 -0.104
199 rsk1_t2 ~ usevap1_t2 0.598 -0.177 -0.177 -0.177 -0.177
200 rsk1_t2 ~ Refusal_t2 1.491 0.076 0.045 0.067 0.067
201 rsk1_t2 ~ knovap_t2 0.008 -0.246 -0.246 -0.066 -0.066
202 rsk1_t2 ~ attnic_t2 12.317 0.417 0.417 0.570 0.570
203 rsk1_t2 ~ usevap1_t1 3.478 -0.056 -0.056 -0.097 -0.085
204 rsk1_t2 ~ Refusal_t1 0.455 0.036 0.024 0.037 0.037
205 rsk1_t2 ~ knovap_t1 0.008 -0.019 -0.019 -0.005 -0.028
206 rsk1_t2 ~ attnic_t1 12.317 0.162 0.162 0.209 0.244
207 attnic_t2 ~ usevap1_t2 11.246 -1.027 -1.027 -0.749 -0.749
208 attnic_t2 ~ Refusal_t2 11.670 0.285 0.167 0.184 0.184
209 attnic_t2 ~ knovap_t2 0.033 -0.647 -0.647 -0.127 -0.127
210 attnic_t2 ~ rsk1_t2 9.845 1.133 1.133 0.828 0.828
211 attnic_t2 ~ usevap1_t1 0.011 0.004 0.004 0.005 0.005
212 attnic_t2 ~ Refusal_t1 2.162 0.106 0.071 0.078 0.078
213 attnic_t2 ~ knovap_t1 0.033 -0.049 -0.049 -0.009 -0.055
214 attnic_t2 ~ rsk1_t1 9.844 0.252 0.252 0.182 0.278
215 usevap1_t1 ~ usevap1_t2 0.885 0.275 0.275 0.160 0.160
216 usevap1_t1 ~ Refusal_t2 4.237 -0.239 -0.140 -0.123 -0.123
217 usevap1_t1 ~ knovap_t2 0.074 -0.097 -0.097 -0.015 -0.015
218 usevap1_t1 ~ rsk1_t2 2.281 -0.141 -0.141 -0.082 -0.082
219 usevap1_t1 ~ attnic_t2 0.582 -0.050 -0.050 -0.040 -0.040
220 usevap1_t1 ~ Refusal_t1 0.692 0.084 0.056 0.049 0.049
221 usevap1_t1 ~ rapd 0.000 0.000 0.000 0.000 0.000
222 usevap1_t1 ~ knovap_t1 0.000 0.000 0.000 0.000 0.000
223 usevap1_t1 ~ rsk1_t1 0.000 0.000 0.000 0.000 0.000
224 usevap1_t1 ~ attnic_t1 0.000 0.000 0.000 0.000 0.000
225 Refusal_t1 ~ usevap1_t2 9.357 -0.239 -0.357 -0.236 -0.236
226 Refusal_t1 ~ Refusal_t2 16.359 3.291 2.879 2.879 2.879
227 Refusal_t1 ~ knovap_t2 5.325 0.526 0.787 0.141 0.141
228 Refusal_t1 ~ rsk1_t2 8.209 0.176 0.263 0.175 0.175
229 Refusal_t1 ~ attnic_t2 11.999 0.156 0.233 0.211 0.211
230 Refusal_t1 ~ usevap1_t1 0.029 0.006 0.009 0.010 0.009
231 Refusal_t1 ~ rapd 16.358 0.883 1.320 0.247 1.320
232 Refusal_t1 ~ knovap_t1 8.550 0.702 1.049 0.178 1.049
233 Refusal_t1 ~ rsk1_t1 12.382 0.219 0.328 0.214 0.328
234 Refusal_t1 ~ attnic_t1 16.755 0.195 0.292 0.249 0.292
235 rapd ~ usevap1_t2 4.303 -0.033 -0.033 -0.117 -0.117
236 rapd ~ Refusal_t2 4.474 0.068 0.040 0.214 0.214
237 rapd ~ knovap_t2 0.870 0.218 0.218 0.208 0.208
238 rapd ~ rsk1_t2 3.926 -0.113 -0.113 -0.402 -0.402
239 rapd ~ attnic_t2 1.398 -0.054 -0.054 -0.262 -0.262
240 rapd ~ usevap1_t1 0.000 0.000 0.000 0.000 0.000
241 rapd ~ Refusal_t1 8.301 0.047 0.032 0.169 0.169
242 rapd ~ knovap_t1 0.000 0.000 0.000 0.000 0.000
243 rapd ~ rsk1_t1 0.000 0.000 0.000 0.000 0.000
244 rapd ~ attnic_t1 0.000 0.000 0.000 0.000 0.000
245 knovap_t1 ~ usevap1_t2 0.940 0.014 0.014 0.054 0.054
246 knovap_t1 ~ Refusal_t2 1.570 -0.022 -0.013 -0.075 -0.075
247 knovap_t1 ~ knovap_t2 0.873 -0.195 -0.195 -0.206 -0.206
248 knovap_t1 ~ rsk1_t2 0.044 -0.003 -0.003 -0.011 -0.011
249 knovap_t1 ~ attnic_t2 0.302 -0.005 -0.005 -0.029 -0.029
250 knovap_t1 ~ usevap1_t1 0.000 0.000 0.000 0.000 0.000
251 knovap_t1 ~ Refusal_t1 4.396 0.032 0.021 0.125 0.125
252 knovap_t1 ~ rapd 0.000 0.000 0.000 0.000 0.000
253 knovap_t1 ~ rsk1_t1 0.000 0.000 0.000 0.000 0.000
254 knovap_t1 ~ attnic_t1 0.000 0.000 0.000 0.000 0.000
255 rsk1_t1 ~ usevap1_t2 2.468 -0.080 -0.080 -0.080 -0.080
256 rsk1_t1 ~ Refusal_t2 4.156 0.125 0.073 0.111 0.111
257 rsk1_t1 ~ knovap_t2 1.379 0.220 0.220 0.060 0.060
258 rsk1_t1 ~ rsk1_t2 0.204 0.040 0.040 0.040 0.040
259 rsk1_t1 ~ attnic_t2 6.593 0.088 0.088 0.122 0.122
260 rsk1_t1 ~ usevap1_t1 0.000 0.000 0.000 0.000 0.000
261 rsk1_t1 ~ Refusal_t1 1.767 0.071 0.047 0.072 0.072
262 rsk1_t1 ~ rapd 0.000 0.000 0.000 0.000 0.000
263 rsk1_t1 ~ knovap_t1 0.000 0.000 0.000 0.000 0.000
264 rsk1_t1 ~ attnic_t1 0.000 0.000 0.000 0.000 0.000
265 attnic_t1 ~ usevap1_t2 2.763 -0.110 -0.110 -0.085 -0.085
266 attnic_t1 ~ Refusal_t2 4.482 0.169 0.099 0.116 0.116
267 attnic_t1 ~ knovap_t2 1.387 -0.288 -0.288 -0.060 -0.060
268 attnic_t1 ~ rsk1_t2 6.070 0.157 0.157 0.122 0.122
269 attnic_t1 ~ attnic_t2 0.107 -0.029 -0.029 -0.031 -0.031
270 attnic_t1 ~ usevap1_t1 0.000 0.000 0.000 0.000 0.000
271 attnic_t1 ~ Refusal_t1 7.074 0.185 0.124 0.145 0.145
272 attnic_t1 ~ rapd 0.000 0.000 0.000 0.000 0.000
273 attnic_t1 ~ knovap_t1 0.000 0.000 0.000 0.000 0.000
274 attnic_t1 ~ rsk1_t1 0.000 0.000 0.000 0.000 0.000Vaping_Indirect <- '
## Latent Variables ##
# POS_coping_t1 =~ cope2_t1 + cope5_t1 + cope7_t1
# POS_coping_t2 =~ cope2_t2 + cope5_t2 + cope7_t2
# Neg_coping_t1 =~ cope1_t1 + cope3_t1 + cope4_t1
#Neg_coping_t2 =~ cope1_t2 + cope3_t2 + cope4_t2
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
# Time 1 covariances
#rsvap1_t1 ~~ rsvap2_t1
#rsvap1_t1 ~~ rsvap3_t1
rsvap1_t1 ~~ rsvap4_t1
#rsvap1_t1 ~~ rsvap5_t1
#rsvap2_t1 ~~ rsvap3_t1
#rsvap2_t1 ~~ rsvap4_t1
rsvap2_t1 ~~ rsvap5_t1
#rsvap3_t1 ~~ rsvap4_t1
rsvap3_t1 ~~ rsvap5_t1
#rsvap4_t1 ~~ rsvap5_t1
# Time 2 covariances
#rsvap1_t2 ~~ rsvap2_t2
#rsvap1_t2 ~~ rsvap3_t2
rsvap1_t2 ~~ rsvap4_t2
#rsvap1_t2 ~~ rsvap5_t2
#rsvap2_t2 ~~ rsvap3_t2
#rsvap2_t2 ~~ rsvap4_t2
rsvap2_t2 ~~ rsvap5_t2
#rsvap3_t2 ~~ rsvap4_t2
rsvap3_t2 ~~ rsvap5_t2
#rsvap4_t2 ~~ rsvap5_t2
## Regressions ##
usevap1_t2 ~ a*usevap1_t1 + b*rsk1_t2 + c*knovap_t2 + d*Refusal_t2 + e*attnic_t2 + t*rapd
'
Vaping_Indirect_Fit <- sem(Vaping_Indirect, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",
mimic = "Mplus",
)
summary(Vaping_Indirect_Fit, fit.measures = TRUE, standardized = TRUE)lavaan 0.6-19 ended normally after 71 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 45
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 306.519 244.793
Degrees of freedom 87 87
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.252
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2193.504 1486.989
Degrees of freedom 110 110
P-value 0.000 0.000
Scaling correction factor 1.475
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.895 0.885
Tucker-Lewis Index (TLI) 0.867 0.855
Robust Comparative Fit Index (CFI) 0.906
Robust Tucker-Lewis Index (TLI) 0.881
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3660.597 -3660.597
Scaling correction factor 1.843
for the MLR correction
Loglikelihood unrestricted model (H1) -3507.338 -3507.338
Scaling correction factor 1.454
for the MLR correction
Akaike (AIC) 7411.194 7411.194
Bayesian (BIC) 7578.312 7578.312
Sample-size adjusted Bayesian (SABIC) 7435.595 7435.595
Root Mean Square Error of Approximation:
RMSEA 0.091 0.077
90 Percent confidence interval - lower 0.080 0.067
90 Percent confidence interval - upper 0.102 0.088
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.954 0.346
Robust RMSEA 0.085
90 Percent confidence interval - lower 0.072
90 Percent confidence interval - upper 0.099
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.757
Standardized Root Mean Square Residual:
SRMR 0.106 0.106
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
Refusal_t1 =~
rsvap1_t1 1.000 0.683 0.736
rsvap2_t1 1.111 0.129 8.634 0.000 0.759 0.672
rsvap3_t1 1.365 0.144 9.489 0.000 0.932 0.901
rsvap4_t1 0.922 0.055 16.855 0.000 0.630 0.692
rsvap5_t1 1.004 0.148 6.783 0.000 0.686 0.597
Refusal_t2 =~
rsvap1_t2 1.000 0.614 0.713
rsvap2_t2 1.357 0.167 8.137 0.000 0.833 0.794
rsvap3_t2 1.295 0.175 7.401 0.000 0.795 0.810
rsvap4_t2 1.025 0.086 11.941 0.000 0.629 0.674
rsvap5_t2 1.219 0.180 6.780 0.000 0.748 0.703
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
usevap1_t2 ~
usevap1_t1 (a) -0.040 0.027 -1.496 0.135 -0.040 -0.069
rsk1_t2 (b) -0.061 0.069 -0.888 0.374 -0.061 -0.063
knovap_t2 (c) -0.235 0.296 -0.794 0.427 -0.235 -0.064
Refusal_t2 (d) -0.254 0.089 -2.845 0.004 -0.156 -0.238
attnic_t2 (e) -0.047 0.056 -0.837 0.403 -0.047 -0.067
rapd (t) -0.394 0.295 -1.333 0.182 -0.394 -0.112
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 ~~
.rsvap4_t1 0.277 0.058 4.741 0.000 0.277 0.672
.rsvap2_t1 ~~
.rsvap5_t1 0.253 0.071 3.545 0.000 0.253 0.328
.rsvap3_t1 ~~
.rsvap5_t1 0.088 0.048 1.821 0.069 0.088 0.212
.rsvap1_t2 ~~
.rsvap4_t2 0.271 0.056 4.826 0.000 0.271 0.652
.rsvap2_t2 ~~
.rsvap5_t2 0.124 0.068 1.832 0.067 0.124 0.257
.rsvap3_t2 ~~
.rsvap5_t2 0.097 0.063 1.536 0.124 0.097 0.224
Refusal_t1 ~~
Refusal_t2 0.229 0.049 4.694 0.000 0.547 0.547
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 3.442 0.053 64.592 0.000 3.442 3.711
.rsvap2_t1 2.974 0.065 45.872 0.000 2.974 2.635
.rsvap3_t1 3.122 0.059 52.516 0.000 3.122 3.017
.rsvap4_t1 3.439 0.052 65.820 0.000 3.439 3.781
.rsvap5_t1 2.954 0.066 44.786 0.000 2.954 2.572
.rsvap1_t2 3.432 0.049 69.432 0.000 3.432 3.989
.rsvap2_t2 3.145 0.060 52.176 0.000 3.145 2.997
.rsvap3_t2 3.267 0.056 58.000 0.000 3.267 3.332
.rsvap4_t2 3.426 0.054 63.875 0.000 3.426 3.670
.rsvap5_t2 3.155 0.061 51.566 0.000 3.155 2.964
.usevap1_t2 1.169 0.484 2.416 0.016 1.169 1.782
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 0.394 0.062 6.396 0.000 0.394 0.458
.rsvap2_t1 0.697 0.091 7.623 0.000 0.697 0.548
.rsvap3_t1 0.202 0.057 3.521 0.000 0.202 0.189
.rsvap4_t1 0.431 0.059 7.360 0.000 0.431 0.521
.rsvap5_t1 0.849 0.098 8.688 0.000 0.849 0.644
.rsvap1_t2 0.364 0.058 6.248 0.000 0.364 0.491
.rsvap2_t2 0.407 0.074 5.483 0.000 0.407 0.370
.rsvap3_t2 0.330 0.065 5.103 0.000 0.330 0.343
.rsvap4_t2 0.476 0.068 7.016 0.000 0.476 0.546
.rsvap5_t2 0.573 0.101 5.656 0.000 0.573 0.506
.usevap1_t2 0.391 0.086 4.547 0.000 0.391 0.907
Refusal_t1 0.466 0.096 4.868 0.000 1.000 1.000
Refusal_t2 0.377 0.085 4.454 0.000 1.000 1.000modindices(Vaping_Indirect_Fit, sort = TRUE) lhs op rhs mi epc sepc.lv sepc.all sepc.nox
151 Refusal_t2 ~ attnic_t2 19.410 0.163 0.265 0.246 0.265
157 attnic_t2 ~ Refusal_t2 16.437 0.345 0.212 0.228 0.228
153 attnic_t2 ~ usevap1_t2 16.437 -1.356 -1.356 -0.960 -0.960
148 Refusal_t2 ~ usevap1_t1 11.604 -0.103 -0.167 -0.190 -0.167
115 rsvap5_t1 ~~ rsvap5_t2 10.071 0.111 0.111 0.160 0.160
149 Refusal_t2 ~ rsk1_t2 9.159 0.154 0.251 0.169 0.251
92 rsvap2_t1 ~~ rsvap2_t2 9.109 0.100 0.100 0.188 0.188
118 rsvap1_t2 ~~ rsvap3_t2 8.591 -0.061 -0.061 -0.176 -0.176
108 rsvap4_t1 ~~ rsvap4_t2 8.319 0.043 0.043 0.094 0.094
106 rsvap4_t1 ~~ rsvap2_t2 7.111 -0.052 -0.052 -0.124 -0.124
124 rsvap3_t2 ~~ rsvap4_t2 6.272 0.055 0.055 0.140 0.140
126 rsvap4_t2 ~~ rsvap5_t2 5.860 -0.055 -0.055 -0.104 -0.104
159 rapd ~ usevap1_t2 5.816 -0.178 -0.178 -0.624 -0.624
163 rapd ~ Refusal_t2 5.816 0.045 0.028 0.148 0.148
93 rsvap2_t1 ~~ rsvap3_t2 5.284 -0.071 -0.071 -0.148 -0.148
119 rsvap1_t2 ~~ rsvap5_t2 5.204 0.048 0.048 0.106 0.106
79 Refusal_t2 =~ rsvap5_t1 4.328 0.251 0.154 0.134 0.134
128 rsvap5_t2 ~~ usevap1_t2 4.122 0.054 0.054 0.113 0.113
141 knovap_t2 ~ usevap1_t2 3.901 -0.138 -0.138 -0.507 -0.507
144 knovap_t2 ~ Refusal_t2 3.901 0.035 0.022 0.121 0.121
98 rsvap3_t1 ~~ rsvap1_t2 3.899 -0.034 -0.034 -0.126 -0.126
114 rsvap5_t1 ~~ rsvap4_t2 3.169 -0.046 -0.046 -0.072 -0.072
100 rsvap3_t1 ~~ rsvap3_t2 3.143 0.044 0.044 0.169 0.169
80 rsvap1_t1 ~~ rsvap2_t1 3.089 0.044 0.044 0.084 0.084
82 rsvap1_t1 ~~ rsvap5_t1 3.054 -0.045 -0.045 -0.078 -0.078
90 rsvap2_t1 ~~ rsvap4_t1 2.941 -0.042 -0.042 -0.076 -0.076
150 Refusal_t2 ~ knovap_t2 2.920 0.328 0.534 0.095 0.534
132 usevap1_t1 ~ Refusal_t2 2.861 -0.194 -0.119 -0.105 -0.105
129 usevap1_t1 ~ usevap1_t2 2.861 0.763 0.763 0.440 0.440
121 rsvap2_t2 ~~ rsvap3_t2 1.853 0.094 0.094 0.256 0.256
152 Refusal_t2 ~ rapd 1.641 0.235 0.382 0.072 0.382
110 rsvap4_t1 ~~ usevap1_t2 1.622 -0.022 -0.022 -0.055 -0.055
75 Refusal_t2 =~ rsvap1_t1 1.550 -0.080 -0.049 -0.053 -0.053
123 rsvap2_t2 ~~ usevap1_t2 1.502 0.032 0.032 0.080 0.080
77 Refusal_t2 =~ rsvap3_t1 1.387 -0.132 -0.081 -0.078 -0.078
96 rsvap2_t1 ~~ usevap1_t2 1.305 0.034 0.034 0.065 0.065
103 rsvap3_t1 ~~ usevap1_t2 1.300 -0.026 -0.026 -0.094 -0.094
71 Refusal_t1 =~ rsvap2_t2 1.206 -0.098 -0.067 -0.064 -0.064
74 Refusal_t1 =~ rsvap5_t2 1.195 0.100 0.068 0.064 0.064
138 rsk1_t2 ~ Refusal_t2 1.035 0.061 0.038 0.056 0.056
135 rsk1_t2 ~ usevap1_t2 1.035 -0.240 -0.240 -0.234 -0.234
127 rsvap4_t2 ~~ usevap1_t2 0.997 -0.019 -0.019 -0.044 -0.044
117 rsvap1_t2 ~~ rsvap2_t2 0.970 0.021 0.021 0.056 0.056
83 rsvap1_t1 ~~ rsvap1_t2 0.924 0.012 0.012 0.033 0.033
104 rsvap4_t1 ~~ rsvap5_t1 0.905 0.023 0.023 0.038 0.038
120 rsvap1_t2 ~~ usevap1_t2 0.818 -0.015 -0.015 -0.041 -0.041
87 rsvap1_t1 ~~ rsvap5_t2 0.723 -0.017 -0.017 -0.035 -0.035
116 rsvap5_t1 ~~ usevap1_t2 0.709 -0.026 -0.026 -0.045 -0.045
122 rsvap2_t2 ~~ rsvap4_t2 0.665 -0.019 -0.019 -0.043 -0.043
78 Refusal_t2 =~ rsvap4_t1 0.665 0.053 0.032 0.035 0.035
88 rsvap1_t1 ~~ usevap1_t2 0.624 0.014 0.014 0.035 0.035
89 rsvap2_t1 ~~ rsvap3_t1 0.573 -0.060 -0.060 -0.160 -0.160
147 Refusal_t2 ~ usevap1_t2 0.537 0.069 0.112 0.073 0.073
70 Refusal_t1 =~ rsvap1_t2 0.450 -0.037 -0.025 -0.029 -0.029
109 rsvap4_t1 ~~ rsvap5_t2 0.427 -0.013 -0.013 -0.027 -0.027
101 rsvap3_t1 ~~ rsvap4_t2 0.391 -0.012 -0.012 -0.039 -0.039
73 Refusal_t1 =~ rsvap4_t2 0.373 0.038 0.026 0.027 0.027
85 rsvap1_t1 ~~ rsvap3_t2 0.371 -0.011 -0.011 -0.030 -0.030
102 rsvap3_t1 ~~ rsvap5_t2 0.361 0.016 0.016 0.048 0.048
86 rsvap1_t1 ~~ rsvap4_t2 0.312 -0.008 -0.008 -0.019 -0.019
105 rsvap4_t1 ~~ rsvap1_t2 0.301 0.007 0.007 0.018 0.018
81 rsvap1_t1 ~~ rsvap3_t1 0.266 0.014 0.014 0.048 0.048
76 Refusal_t2 =~ rsvap2_t1 0.256 0.058 0.036 0.032 0.032
99 rsvap3_t1 ~~ rsvap2_t2 0.251 -0.013 -0.013 -0.046 -0.046
112 rsvap5_t1 ~~ rsvap2_t2 0.206 0.015 0.015 0.026 0.026
95 rsvap2_t1 ~~ rsvap5_t2 0.129 -0.012 -0.012 -0.019 -0.019
97 rsvap3_t1 ~~ rsvap4_t1 0.087 0.007 0.007 0.025 0.025
91 rsvap2_t1 ~~ rsvap1_t2 0.042 0.005 0.005 0.009 0.009
107 rsvap4_t1 ~~ rsvap3_t2 0.033 0.003 0.003 0.009 0.009
113 rsvap5_t1 ~~ rsvap3_t2 0.020 0.005 0.005 0.009 0.009
72 Refusal_t1 =~ rsvap3_t2 0.018 -0.011 -0.008 -0.008 -0.008
125 rsvap3_t2 ~~ usevap1_t2 0.014 -0.003 -0.003 -0.008 -0.008
111 rsvap5_t1 ~~ rsvap1_t2 0.013 -0.003 -0.003 -0.005 -0.005
94 rsvap2_t1 ~~ rsvap4_t2 0.005 0.002 0.002 0.003 0.003
84 rsvap1_t1 ~~ rsvap2_t2 0.000 0.000 0.000 0.000 0.000RAPD Path Model moderated by Gender
Vaping_Indirect_Gender <- '
## Latent Variables ##
# POS_coping_t1 =~ cope2_t1 + cope5_t1 + cope7_t1
# POS_coping_t2 =~ cope2_t2 + cope5_t2 + cope7_t2
# Neg_coping_t1 =~ cope1_t1 + cope3_t1 + cope4_t1
#Neg_coping_t2 =~ cope1_t2 + cope3_t2 + cope4_t2
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
## Regressions ##
usevap1_t2 ~ a*usevap1_t1 + 0*rsk1_t2 + 0*knovap_t2 + d*Refusal_t2 + 0*attnic_t2 + t*rapd
#rsk1_t2 ~ h*rsk1_t1 + i*rapd
#knovap_t2 ~ j*knovap_t1 + k*rapd
Refusal_t2 ~ l*Refusal_t1 + m*rapd
#attnic_t2 ~ n*attnic_t1 + o*rapd
rsvap1_t2 ~~ rsvap4_t2
rsvap1_t1 ~~ rsvap4_t1
rsvap3_t2 ~~ rsvap5_t2
rsvap1_t1 ~~ rsvap4_t1
rsvap1_t2 ~~ rsvap4_t2
rsvap2_t2 ~~ rsvap5_t2
rsvap2_t2 ~~ rsvap5_t2
#Indirect Effects
#via_risk := b*i
#via_know := c*k
via_Refusal := d*m
#via_attitudes := e*o
#Total Effect
total := t +(d*m)
'
Vaping_Indirect_Fit_Gender <- sem(Vaping_Indirect_Gender, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",mimic = "Mplus",
group = "male_binary")
summary(Vaping_Indirect_Fit_Gender, fit.measures = TRUE, standardized = TRUE, ci = TRUE)lavaan 0.6-19 ended normally after 80 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 84
Number of equality constraints 24
Number of observations per group:
male 153
not male 150
Number of missing patterns per group:
male 1
not male 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 482.119 410.247
Degrees of freedom 204 204
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.175
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
male 196.086 196.086
not male 214.161 214.161
Model Test Baseline Model:
Test statistic 2367.632 1728.279
Degrees of freedom 220 220
P-value 0.000 0.000
Scaling correction factor 1.370
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.870 0.863
Tucker-Lewis Index (TLI) 0.860 0.853
Robust Comparative Fit Index (CFI) 0.892
Robust Tucker-Lewis Index (TLI) 0.884
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3642.594 -3642.594
Scaling correction factor 1.468
for the MLR correction
Loglikelihood unrestricted model (H1) -3401.534 -3401.534
Scaling correction factor 1.375
for the MLR correction
Akaike (AIC) 7405.187 7405.187
Bayesian (BIC) 7628.011 7628.011
Sample-size adjusted Bayesian (SABIC) 7437.723 7437.723
Root Mean Square Error of Approximation:
RMSEA 0.095 0.082
90 Percent confidence interval - lower 0.084 0.071
90 Percent confidence interval - upper 0.106 0.092
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.987 0.613
Robust RMSEA 0.085
90 Percent confidence interval - lower 0.072
90 Percent confidence interval - upper 0.098
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.741
Standardized Root Mean Square Residual:
SRMR 0.115 0.115
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Group 1 [male]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
Refusal_t1 =~
rsvp1_1 1.000 1.000 1.000
rsvp2_1 (.p2.) 1.227 0.159 7.715 0.000 0.915 1.539
rsvp3_1 (.p3.) 1.392 0.125 11.168 0.000 1.148 1.637
rsvp4_1 (.p4.) 0.939 0.047 19.930 0.000 0.846 1.031
rsvp5_1 (.p5.) 1.237 0.166 7.470 0.000 0.913 1.562
Refusal_t2 =~
rsvp1_2 1.000 1.000 1.000
rsvp2_2 (.p7.) 1.361 0.169 8.034 0.000 1.029 1.693
rsvp3_2 (.p8.) 1.294 0.170 7.603 0.000 0.961 1.628
rsvp4_2 (.p9.) 1.015 0.064 15.944 0.000 0.890 1.140
rsvp5_2 (.10.) 1.214 0.187 6.510 0.000 0.849 1.580
Std.lv Std.all
0.649 0.725
0.796 0.677
0.903 0.893
0.609 0.698
0.803 0.672
0.673 0.734
0.916 0.824
0.871 0.818
0.683 0.723
0.817 0.699
Regressions:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
usevap1_t2 ~
usevap1_t1 (a) -0.039 0.026 -1.466 0.143 -0.091 0.013
rsk1_t2 0.000 0.000 0.000
knovap_t2 0.000 0.000 0.000
Refusal_t2 (d) -0.282 0.103 -2.743 0.006 -0.483 -0.081
attnic_t2 0.000 0.000 0.000
rapd (t) -0.215 0.272 -0.790 0.429 -0.749 0.318
Refusal_t2 ~
Refusal_t1 (l) 0.523 0.093 5.637 0.000 0.341 0.704
rapd (m) 0.316 0.254 1.242 0.214 -0.183 0.814
Std.lv Std.all
-0.039 -0.076
0.000 0.000
0.000 0.000
-0.190 -0.336
0.000 0.000
-0.215 -0.074
0.504 0.504
0.469 0.091
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t2 ~~
.rsvap4_t2 0.290 0.079 3.666 0.000 0.135 0.445
.rsvap1_t1 ~~
.rsvap4_t1 0.254 0.061 4.147 0.000 0.134 0.374
.rsvap3_t2 ~~
.rsvap5_t2 0.091 0.089 1.026 0.305 -0.083 0.266
.rsvap2_t2 ~~
.rsvap5_t2 0.078 0.105 0.740 0.459 -0.129 0.285
Std.lv Std.all
0.290 0.712
0.254 0.659
0.091 0.179
0.078 0.148
Intercepts:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvp1_1 (.51.) 3.431 0.068 50.455 0.000 3.298 3.564
.rsvp2_1 (.52.) 2.950 0.082 36.005 0.000 2.789 3.110
.rsvp3_1 (.53.) 3.096 0.081 38.260 0.000 2.937 3.254
.rsvp4_1 (.54.) 3.429 0.066 51.648 0.000 3.299 3.559
.rsvp5_1 (.55.) 2.935 0.082 35.868 0.000 2.774 3.095
.rsvp1_2 (.56.) 3.121 0.259 12.051 0.000 2.613 3.629
.rsvp2_2 (.57.) 2.717 0.328 8.289 0.000 2.074 3.359
.rsvp3_2 (.58.) 2.863 0.315 9.091 0.000 2.246 3.481
.rsvp4_2 (.59.) 3.111 0.259 12.004 0.000 2.603 3.619
.rsvp5_2 (.60.) 2.796 0.296 9.456 0.000 2.216 3.375
.usvp1_2 (.61.) 0.482 0.315 1.530 0.126 -0.136 1.100
Std.lv Std.all
3.431 3.831
2.950 2.508
3.096 3.060
3.429 3.932
2.935 2.457
3.121 3.403
2.717 2.444
2.863 2.690
3.111 3.293
2.796 2.392
0.482 0.853
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 0.381 0.065 5.834 0.000 0.253 0.509
.rsvap2_t1 0.750 0.131 5.728 0.000 0.493 1.006
.rsvap3_t1 0.208 0.066 3.160 0.002 0.079 0.337
.rsvap4_t1 0.390 0.066 5.945 0.000 0.261 0.518
.rsvap5_t1 0.782 0.115 6.821 0.000 0.557 1.006
.rsvap1_t2 0.388 0.081 4.824 0.000 0.231 0.546
.rsvap2_t2 0.397 0.108 3.682 0.000 0.186 0.608
.rsvap3_t2 0.375 0.086 4.380 0.000 0.207 0.542
.rsvap4_t2 0.427 0.081 5.255 0.000 0.267 0.586
.rsvap5_t2 0.698 0.145 4.832 0.000 0.415 0.982
.usevap1_t2 0.279 0.108 2.586 0.010 0.067 0.490
Refusal_t1 0.421 0.100 4.229 0.000 0.226 0.616
.Refusal_t2 0.334 0.095 3.510 0.000 0.148 0.521
Std.lv Std.all
0.381 0.475
0.750 0.542
0.208 0.203
0.390 0.512
0.782 0.548
0.388 0.462
0.397 0.321
0.375 0.331
0.427 0.478
0.698 0.511
0.279 0.872
1.000 1.000
0.738 0.738
Group 2 [not male]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
Refusal_t1 =~
rsvp1_1 1.000 1.000 1.000
rsvp2_1 (.p2.) 1.227 0.159 7.715 0.000 0.915 1.539
rsvp3_1 (.p3.) 1.392 0.125 11.168 0.000 1.148 1.637
rsvp4_1 (.p4.) 0.939 0.047 19.930 0.000 0.846 1.031
rsvp5_1 (.p5.) 1.237 0.166 7.470 0.000 0.913 1.562
Refusal_t2 =~
rsvp1_2 1.000 1.000 1.000
rsvp2_2 (.p7.) 1.361 0.169 8.034 0.000 1.029 1.693
rsvp3_2 (.p8.) 1.294 0.170 7.603 0.000 0.961 1.628
rsvp4_2 (.p9.) 1.015 0.064 15.944 0.000 0.890 1.140
rsvp5_2 (.10.) 1.214 0.187 6.510 0.000 0.849 1.580
Std.lv Std.all
0.665 0.691
0.815 0.756
0.925 0.872
0.624 0.656
0.822 0.741
0.545 0.688
0.741 0.756
0.705 0.793
0.553 0.606
0.661 0.706
Regressions:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
usevap1_t2 ~
usevap1_t1 (a) -0.039 0.026 -1.466 0.143 -0.091 0.013
rsk1_t2 0.000 0.000 0.000
knovap_t2 0.000 0.000 0.000
Refusal_t2 (d) -0.282 0.103 -2.743 0.006 -0.483 -0.081
attnic_t2 0.000 0.000 0.000
rapd (t) -0.215 0.272 -0.790 0.429 -0.749 0.318
Refusal_t2 ~
Refusal_t1 (l) 0.523 0.093 5.637 0.000 0.341 0.704
rapd (m) 0.316 0.254 1.242 0.214 -0.183 0.814
Std.lv Std.all
-0.039 -0.061
0.000 0.000
0.000 0.000
-0.154 -0.207
0.000 0.000
-0.215 -0.052
0.638 0.638
0.580 0.104
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t2 ~~
.rsvap4_t2 0.249 0.067 3.693 0.000 0.117 0.381
.rsvap1_t1 ~~
.rsvap4_t1 0.358 0.086 4.146 0.000 0.189 0.527
.rsvap3_t2 ~~
.rsvap5_t2 0.104 0.060 1.744 0.081 -0.013 0.222
.rsvap2_t2 ~~
.rsvap5_t2 0.164 0.068 2.400 0.016 0.030 0.297
Std.lv Std.all
0.249 0.597
0.358 0.718
0.104 0.291
0.164 0.385
Intercepts:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvp1_1 (.51.) 3.431 0.068 50.455 0.000 3.298 3.564
.rsvp2_1 (.52.) 2.950 0.082 36.005 0.000 2.789 3.110
.rsvp3_1 (.53.) 3.096 0.081 38.260 0.000 2.937 3.254
.rsvp4_1 (.54.) 3.429 0.066 51.648 0.000 3.299 3.559
.rsvp5_1 (.55.) 2.935 0.082 35.868 0.000 2.774 3.095
.rsvp1_2 (.56.) 3.121 0.259 12.051 0.000 2.613 3.629
.rsvp2_2 (.57.) 2.717 0.328 8.289 0.000 2.074 3.359
.rsvp3_2 (.58.) 2.863 0.315 9.091 0.000 2.246 3.481
.rsvp4_2 (.59.) 3.111 0.259 12.004 0.000 2.603 3.619
.rsvp5_2 (.60.) 2.796 0.296 9.456 0.000 2.216 3.375
.usvp1_2 (.61.) 0.482 0.315 1.530 0.126 -0.136 1.100
Rfsl_t1 0.034 0.081 0.426 0.670 -0.124 0.193
.Rfsl_t2 -0.004 0.071 -0.057 0.955 -0.142 0.134
Std.lv Std.all
3.431 3.566
2.950 2.736
3.096 2.916
3.429 3.607
2.935 2.644
3.121 3.944
2.717 2.774
2.863 3.223
3.111 3.410
2.796 2.985
0.482 0.650
0.052 0.052
-0.007 -0.007
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 0.484 0.090 5.371 0.000 0.307 0.661
.rsvap2_t1 0.497 0.112 4.453 0.000 0.278 0.716
.rsvap3_t1 0.271 0.082 3.305 0.001 0.110 0.431
.rsvap4_t1 0.514 0.083 6.188 0.000 0.352 0.677
.rsvap5_t1 0.556 0.119 4.660 0.000 0.322 0.789
.rsvap1_t2 0.330 0.067 4.924 0.000 0.198 0.461
.rsvap2_t2 0.410 0.084 4.874 0.000 0.245 0.575
.rsvap3_t2 0.293 0.072 4.077 0.000 0.152 0.434
.rsvap4_t2 0.527 0.095 5.561 0.000 0.341 0.713
.rsvap5_t2 0.440 0.101 4.349 0.000 0.241 0.638
.usevap1_t2 0.523 0.152 3.448 0.001 0.226 0.820
Refusal_t1 0.442 0.103 4.295 0.000 0.240 0.643
.Refusal_t2 0.173 0.051 3.354 0.001 0.072 0.274
Std.lv Std.all
0.484 0.523
0.497 0.428
0.271 0.240
0.514 0.569
0.556 0.451
0.330 0.526
0.410 0.428
0.293 0.371
0.527 0.633
0.440 0.501
0.523 0.950
1.000 1.000
0.582 0.582
Defined Parameters:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
via_Refusal -0.089 0.078 -1.141 0.254 -0.242 0.064
total -0.304 0.304 -1.001 0.317 -0.900 0.291
Std.lv Std.all
-0.089 -0.031
-0.304 -0.104#modindices(Vaping_Indirect_Fit_Gender, sort = TRUE)RAPD Vaping Path Model moderated by race
Vaping_Indirect_Race <- '
## Latent Variables ##
# POS_coping_t1 =~ cope2_t1 + cope5_t1 + cope7_t1
# POS_coping_t2 =~ cope2_t2 + cope5_t2 + cope7_t2
# Neg_coping_t1 =~ cope1_t1 + cope3_t1 + cope4_t1
#Neg_coping_t2 =~ cope1_t2 + cope3_t2 + cope4_t2
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
## Regressions ##
usevap1_t2 ~ a*usevap1_t1 + 0*rsk1_t2 + 0*knovap_t2 + d*Refusal_t2 + 0*attnic_t2 + t*rapd
#rsk1_t2 ~ h*rsk1_t1 + i*rapd
#knovap_t2 ~ j*knovap_t1 + k*rapd
Refusal_t2 ~ l*Refusal_t1 + m*rapd
#attnic_t2 ~ n*attnic_t1 + o*rapd
#Indirect Effects
#via_risk := b*i
#via_know := c*k
via_Refusal := d*m
#via_attitudes := e*o
#Total Effect
total := t + (d*m)
'
Vaping_Indirect_Fit_Race <- sem(Vaping_Indirect_Race, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",mimic = "Mplus",
group = "White_binary", group.equal = c("loadings"))
summary(Vaping_Indirect_Fit_Race, fit.measures = TRUE, standardized = TRUE, ci = TRUE)lavaan 0.6-19 ended normally after 73 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 74
Number of equality constraints 13
Number of observations per group:
not White 119
White 184
Number of missing patterns per group:
not White 1
White 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 740.655 626.404
Degrees of freedom 203 203
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.182
Yuan-Bentler correction (Mplus variant)
Test statistic for each group:
not White 295.712 295.712
White 330.692 330.692
Model Test Baseline Model:
Test statistic 2302.505 1730.473
Degrees of freedom 220 220
P-value 0.000 0.000
Scaling correction factor 1.331
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.742 0.720
Tucker-Lewis Index (TLI) 0.720 0.696
Robust Comparative Fit Index (CFI) 0.759
Robust Tucker-Lewis Index (TLI) 0.739
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3752.091 -3752.091
Scaling correction factor 1.514
for the MLR correction
Loglikelihood unrestricted model (H1) -3381.763 -3381.763
Scaling correction factor 1.334
for the MLR correction
Akaike (AIC) 7626.181 7626.181
Bayesian (BIC) 7852.719 7852.719
Sample-size adjusted Bayesian (SABIC) 7659.259 7659.259
Root Mean Square Error of Approximation:
RMSEA 0.132 0.117
90 Percent confidence interval - lower 0.122 0.108
90 Percent confidence interval - upper 0.143 0.127
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 1.000
Robust RMSEA 0.126
90 Percent confidence interval - lower 0.114
90 Percent confidence interval - upper 0.138
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 1.000
Standardized Root Mean Square Residual:
SRMR 0.126 0.126
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Group 1 [not White]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
Refusal_t1 =~
rsvp1_1 1.000 1.000 1.000
rsvp2_1 (.p2.) 0.787 0.114 6.911 0.000 0.564 1.011
rsvp3_1 (.p3.) 0.939 0.093 10.127 0.000 0.757 1.120
rsvp4_1 (.p4.) 0.991 0.033 30.054 0.000 0.926 1.055
rsvp5_1 (.p5.) 0.722 0.112 6.427 0.000 0.502 0.942
Refusal_t2 =~
rsvp1_2 1.000 1.000 1.000
rsvp2_2 (.p7.) 0.914 0.102 8.984 0.000 0.715 1.114
rsvp3_2 (.p8.) 0.872 0.113 7.742 0.000 0.651 1.093
rsvp4_2 (.p9.) 1.027 0.051 20.071 0.000 0.927 1.128
rsvp5_2 (.10.) 0.818 0.123 6.677 0.000 0.578 1.058
Std.lv Std.all
0.923 0.875
0.727 0.644
0.867 0.777
0.915 0.854
0.667 0.553
0.789 0.834
0.722 0.665
0.688 0.709
0.811 0.845
0.646 0.594
Regressions:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
usevap1_t2 ~
usevap1_t1 (a) -0.042 0.027 -1.540 0.124 -0.096 0.012
rsk1_t2 0.000 0.000 0.000
knovap_t2 0.000 0.000 0.000
Refusal_t2 (d) -0.276 0.081 -3.405 0.001 -0.434 -0.117
attnic_t2 0.000 0.000 0.000
rapd (t) -0.405 0.286 -1.418 0.156 -0.965 0.155
Refusal_t2 ~
Refusal_t1 (l) 0.447 0.077 5.816 0.000 0.296 0.597
rapd (m) 0.379 0.293 1.293 0.196 -0.196 0.954
Std.lv Std.all
-0.042 -0.065
0.000 0.000
0.000 0.000
-0.218 -0.318
0.000 0.000
-0.405 -0.148
0.522 0.522
0.480 0.120
Intercepts:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 3.252 0.097 33.377 0.000 3.061 3.443
.rsvap2_t1 2.672 0.108 24.815 0.000 2.461 2.883
.rsvap3_t1 2.807 0.102 27.403 0.000 2.606 3.007
.rsvap4_t1 3.303 0.094 35.136 0.000 3.118 3.487
.rsvap5_t1 2.672 0.111 24.092 0.000 2.455 2.890
.rsvap1_t2 2.974 0.295 10.091 0.000 2.397 3.552
.rsvap2_t2 2.584 0.271 9.553 0.000 2.054 3.115
.rsvap3_t2 2.767 0.265 10.444 0.000 2.248 3.287
.rsvap4_t2 2.981 0.299 9.964 0.000 2.395 3.568
.rsvap5_t2 2.560 0.247 10.352 0.000 2.075 3.044
.usevap1_t2 0.699 0.325 2.149 0.032 0.062 1.337
Std.lv Std.all
3.252 3.083
2.672 2.369
2.807 2.518
3.303 3.085
2.672 2.216
2.974 3.142
2.584 2.382
2.767 2.849
2.981 3.107
2.560 2.355
0.699 1.023
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 0.261 0.117 2.219 0.026 0.030 0.491
.rsvap2_t1 0.744 0.161 4.630 0.000 0.429 1.059
.rsvap3_t1 0.492 0.152 3.228 0.001 0.193 0.790
.rsvap4_t1 0.310 0.145 2.136 0.033 0.026 0.594
.rsvap5_t1 1.009 0.175 5.781 0.000 0.667 1.352
.rsvap1_t2 0.273 0.125 2.182 0.029 0.028 0.518
.rsvap2_t2 0.656 0.151 4.348 0.000 0.360 0.952
.rsvap3_t2 0.470 0.122 3.853 0.000 0.231 0.708
.rsvap4_t2 0.263 0.102 2.587 0.010 0.064 0.463
.rsvap5_t2 0.764 0.164 4.665 0.000 0.443 1.086
.usevap1_t2 0.404 0.135 2.994 0.003 0.140 0.669
Refusal_t1 0.852 0.147 5.807 0.000 0.565 1.140
.Refusal_t2 0.444 0.094 4.717 0.000 0.259 0.628
Std.lv Std.all
0.261 0.234
0.744 0.585
0.492 0.396
0.310 0.270
1.009 0.694
0.273 0.305
0.656 0.558
0.470 0.498
0.263 0.286
0.764 0.647
0.404 0.865
1.000 1.000
0.713 0.713
Group 2 [White]:
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
Refusal_t1 =~
rsvp1_1 1.000 1.000 1.000
rsvp2_1 (.p2.) 0.787 0.114 6.911 0.000 0.564 1.011
rsvp3_1 (.p3.) 0.939 0.093 10.127 0.000 0.757 1.120
rsvp4_1 (.p4.) 0.991 0.033 30.054 0.000 0.926 1.055
rsvp5_1 (.p5.) 0.722 0.112 6.427 0.000 0.502 0.942
Refusal_t2 =~
rsvp1_2 1.000 1.000 1.000
rsvp2_2 (.p7.) 0.914 0.102 8.984 0.000 0.715 1.114
rsvp3_2 (.p8.) 0.872 0.113 7.742 0.000 0.651 1.093
rsvp4_2 (.p9.) 1.027 0.051 20.071 0.000 0.927 1.128
rsvp5_2 (.10.) 0.818 0.123 6.677 0.000 0.578 1.058
Std.lv Std.all
0.738 0.913
0.581 0.533
0.692 0.750
0.731 0.913
0.533 0.498
0.759 0.939
0.694 0.702
0.662 0.688
0.780 0.863
0.621 0.631
Regressions:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
usevap1_t2 ~
usevap1_t1 (a) -0.042 0.027 -1.540 0.124 -0.096 0.012
rsk1_t2 0.000 0.000 0.000
knovap_t2 0.000 0.000 0.000
Refusal_t2 (d) -0.276 0.081 -3.405 0.001 -0.434 -0.117
attnic_t2 0.000 0.000 0.000
rapd (t) -0.405 0.286 -1.418 0.156 -0.965 0.155
Refusal_t2 ~
Refusal_t1 (l) 0.447 0.077 5.816 0.000 0.296 0.597
rapd (m) 0.379 0.293 1.293 0.196 -0.196 0.954
Std.lv Std.all
-0.042 -0.077
0.000 0.000
0.000 0.000
-0.209 -0.322
0.000 0.000
-0.405 -0.079
0.434 0.434
0.499 0.063
Intercepts:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 3.565 0.059 60.081 0.000 3.449 3.682
.rsvap2_t1 3.168 0.078 40.840 0.000 3.016 3.321
.rsvap3_t1 3.326 0.068 48.931 0.000 3.193 3.459
.rsvap4_t1 3.527 0.060 58.790 0.000 3.410 3.645
.rsvap5_t1 3.136 0.079 39.854 0.000 2.982 3.290
.rsvap1_t2 3.127 0.298 10.501 0.000 2.544 3.711
.rsvap2_t2 2.958 0.268 11.049 0.000 2.433 3.483
.rsvap3_t2 3.066 0.263 11.667 0.000 2.551 3.581
.rsvap4_t2 3.095 0.304 10.178 0.000 2.499 3.691
.rsvap5_t2 3.048 0.248 12.305 0.000 2.563 3.534
.usevap1_t2 0.703 0.317 2.219 0.026 0.082 1.324
Std.lv Std.all
3.565 4.414
3.168 2.908
3.326 3.601
3.527 4.405
3.136 2.931
3.127 3.867
2.958 2.991
3.066 3.187
3.095 3.421
3.048 3.094
0.703 1.080
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 0.108 0.047 2.295 0.022 0.016 0.201
.rsvap2_t1 0.850 0.126 6.729 0.000 0.602 1.097
.rsvap3_t1 0.374 0.076 4.941 0.000 0.225 0.522
.rsvap4_t1 0.107 0.040 2.685 0.007 0.029 0.185
.rsvap5_t1 0.861 0.109 7.910 0.000 0.648 1.074
.rsvap1_t2 0.077 0.034 2.279 0.023 0.011 0.144
.rsvap2_t2 0.496 0.100 4.979 0.000 0.301 0.692
.rsvap3_t2 0.487 0.096 5.067 0.000 0.299 0.676
.rsvap4_t2 0.209 0.055 3.819 0.000 0.102 0.317
.rsvap5_t2 0.585 0.100 5.821 0.000 0.388 0.781
.usevap1_t2 0.374 0.107 3.485 0.000 0.164 0.585
Refusal_t1 0.544 0.109 4.998 0.000 0.331 0.757
.Refusal_t2 0.466 0.101 4.598 0.000 0.267 0.665
Std.lv Std.all
0.108 0.166
0.850 0.716
0.374 0.438
0.107 0.167
0.861 0.752
0.077 0.118
0.496 0.507
0.487 0.526
0.209 0.256
0.585 0.602
0.374 0.884
1.000 1.000
0.808 0.808
Defined Parameters:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
via_Refusal -0.104 0.086 -1.215 0.224 -0.273 0.064
total -0.510 0.316 -1.612 0.107 -1.129 0.110
Std.lv Std.all
-0.104 -0.038
-0.510 -0.187Trying a different approach: Specifying a path model for time 1 and time 2
Vaping_Model_T1 <- '
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
#Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
rsvap1_t1 ~~ rsvap4_t1
rsvap2_t1 ~~ rsvap5_t1
rsvap3_t1 ~~ rsvap5_t1
rsvap2_t1 ~~ rsvap3_t1
rsvap1_t1 ~~ rsvap5_t1
## Regressions ##
usevap1_t1 ~ rsk1_t1 + knovap_t1 + Refusal_t1 + attnic_t1
'
Vaping_Model_T1_Fit <- sem(Vaping_Model_T1, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",mimic = "Mplus")Warning: lavaan->lav_object_post_check():
some estimated ov variances are negativesummary(Vaping_Model_T1_Fit, fit.measures = TRUE, standardized = TRUE, ci = TRUE)lavaan 0.6-19 ended normally after 81 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 26
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 76.148 62.833
Degrees of freedom 19 19
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.212
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 970.665 642.575
Degrees of freedom 33 33
P-value 0.000 0.000
Scaling correction factor 1.511
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.939 0.928
Tucker-Lewis Index (TLI) 0.894 0.875
Robust Comparative Fit Index (CFI) 0.943
Robust Tucker-Lewis Index (TLI) 0.901
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -2209.096 -2209.096
Scaling correction factor 1.487
for the MLR correction
Loglikelihood unrestricted model (H1) -2171.022 -2171.022
Scaling correction factor 1.371
for the MLR correction
Akaike (AIC) 4470.193 4470.193
Bayesian (BIC) 4566.750 4566.750
Sample-size adjusted Bayesian (SABIC) 4484.292 4484.292
Root Mean Square Error of Approximation:
RMSEA 0.100 0.087
90 Percent confidence interval - lower 0.077 0.066
90 Percent confidence interval - upper 0.124 0.109
P-value H_0: RMSEA <= 0.050 0.000 0.003
P-value H_0: RMSEA >= 0.080 0.923 0.728
Robust RMSEA 0.096
90 Percent confidence interval - lower 0.070
90 Percent confidence interval - upper 0.123
P-value H_0: Robust RMSEA <= 0.050 0.003
P-value H_0: Robust RMSEA >= 0.080 0.850
Standardized Root Mean Square Residual:
SRMR 0.103 0.103
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
Refusal_t1 =~
rsvap1_t1 1.000 1.000 1.000
rsvap2_t1 1.462 1.699 0.860 0.390 -1.869 4.793
rsvap3_t1 1.813 2.087 0.869 0.385 -2.278 5.904
rsvap4_t1 0.917 0.058 15.789 0.000 0.803 1.031
rsvap5_t1 1.299 1.492 0.871 0.384 -1.625 4.224
Std.lv Std.all
0.594 0.641
0.869 0.770
1.078 1.041
0.545 0.600
0.772 0.672
Regressions:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
usevap1_t1 ~
rsk1_t1 0.267 0.113 2.357 0.018 0.045 0.490
knovap_t1 -0.326 0.453 -0.719 0.472 -1.215 0.563
Refusal_t1 0.103 0.110 0.936 0.349 -0.113 0.318
attnic_t1 -0.248 0.089 -2.787 0.005 -0.422 -0.073
Std.lv Std.all
0.267 0.154
-0.326 -0.049
0.061 0.054
-0.248 -0.186
Covariances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 ~~
.rsvap4_t1 0.383 0.375 1.020 0.308 -0.353 1.119
.rsvap2_t1 ~~
.rsvap5_t1 0.103 0.790 0.130 0.896 -1.445 1.652
.rsvap3_t1 ~~
.rsvap5_t1 -0.108 0.967 -0.112 0.911 -2.002 1.786
.rsvap2_t1 ~~
.rsvap3_t1 -0.234 1.093 -0.214 0.831 -2.375 1.908
.rsvap1_t1 ~~
.rsvap5_t1 -0.031 0.036 -0.861 0.389 -0.102 0.040
Std.lv Std.all
0.383 0.739
0.103 0.168
-0.108 -0.422
-0.234 -1.079
-0.031 -0.052
Intercepts:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 3.442 0.053 64.592 0.000 3.338 3.547
.rsvap2_t1 2.974 0.065 45.872 0.000 2.847 3.101
.rsvap3_t1 3.122 0.059 52.517 0.000 3.006 3.239
.rsvap4_t1 3.439 0.052 65.820 0.000 3.337 3.541
.rsvap5_t1 2.954 0.066 44.786 0.000 2.825 3.083
.usevap1_t1 1.585 0.608 2.609 0.009 0.394 2.776
Std.lv Std.all
3.442 3.710
2.974 2.635
3.122 3.017
3.439 3.781
2.954 2.571
1.585 1.391
Variances:
Estimate Std.Err z-value P(>|z|) ci.lower ci.upper
.rsvap1_t1 0.507 0.412 1.232 0.218 -0.300 1.315
.rsvap2_t1 0.518 0.897 0.577 0.564 -1.241 2.277
.rsvap3_t1 -0.091 1.352 -0.067 0.947 -2.740 2.559
.rsvap4_t1 0.530 0.349 1.516 0.130 -0.155 1.215
.rsvap5_t1 0.723 0.702 1.031 0.303 -0.652 2.099
.usevap1_t1 1.249 0.084 14.958 0.000 1.086 1.413
Refusal_t1 0.353 0.408 0.866 0.387 -0.447 1.153
Std.lv Std.all
0.507 0.590
0.518 0.407
-0.091 -0.085
0.530 0.641
0.723 0.548
1.249 0.962
1.000 1.000modificationindices(Vaping_Model_T1_Fit, sort = TRUE)Warning in sqrt(var.lhs.value * var.rhs.value): NaNs producedWarning: lavaan->lav_start_check_cov():
starting values imply NaN for a correlation value; variables involved are:
rsvap3_t1 rsvap5_t1 lhs op rhs mi epc sepc.lv sepc.all sepc.nox
54 knovap_t1 ~ Refusal_t1 8.347 0.051 0.031 0.180 0.180
1 Refusal_t1 =~ rsvap1_t1 5.980 0.295 0.175 0.189 0.189
63 attnic_t1 ~ Refusal_t1 5.836 0.200 0.119 0.139 0.139
60 attnic_t1 ~ usevap1_t1 4.180 1.384 1.384 1.847 1.847
42 rsvap2_t1 ~~ usevap1_t1 3.747 0.119 0.119 0.148 0.148
52 knovap_t1 ~ usevap1_t1 3.710 0.283 0.283 1.903 1.903
57 Refusal_t1 ~ rsk1_t1 3.478 0.066 0.112 0.073 0.112
39 rsvap1_t1 ~~ rsvap3_t1 3.287 0.068 0.068 0.096 0.096
47 rsvap5_t1 ~~ usevap1_t1 2.912 -0.112 -0.112 -0.100 -0.100
59 Refusal_t1 ~ attnic_t1 2.844 0.037 0.063 0.054 0.063
41 rsvap2_t1 ~~ rsvap4_t1 2.683 -0.048 -0.048 -0.091 -0.091
40 rsvap1_t1 ~~ usevap1_t1 2.597 -0.056 -0.056 -0.070 -0.070
58 Refusal_t1 ~ knovap_t1 2.261 0.156 0.263 0.045 0.263
46 rsvap4_t1 ~~ usevap1_t1 2.011 0.046 0.046 0.056 0.056
50 rsk1_t1 ~ Refusal_t1 1.888 0.086 0.051 0.078 0.078
48 rsk1_t1 ~ usevap1_t1 1.604 0.653 0.653 1.137 1.137
43 rsvap3_t1 ~~ rsvap4_t1 1.349 0.044 0.044 0.061 0.061
38 rsvap1_t1 ~~ rsvap2_t1 0.745 0.027 0.027 0.053 0.053
45 rsvap4_t1 ~~ rsvap5_t1 0.558 0.040 0.040 0.055 0.055
44 rsvap3_t1 ~~ usevap1_t1 0.017 0.011 0.011 0.010 0.010
56 Refusal_t1 ~ usevap1_t1 0.006 -0.005 -0.008 -0.009 -0.009
37 Refusal_t1 ~1 0.000 0.000 0.000 0.000 0.000
25 knovap_t1 ~~ knovap_t1 0.000 0.000 0.000 0.000 0.000
55 knovap_t1 ~ attnic_t1 0.000 0.000 0.000 0.000 0.000
26 knovap_t1 ~~ attnic_t1 0.000 0.000 0.000 NA 0.000
53 knovap_t1 ~ rsk1_t1 0.000 0.000 0.000 0.000 0.000
62 attnic_t1 ~ knovap_t1 0.000 0.000 0.000 0.000 0.000
24 rsk1_t1 ~~ attnic_t1 0.000 0.000 0.000 NA 0.000
22 rsk1_t1 ~~ rsk1_t1 0.000 0.000 0.000 0.000 0.000
51 rsk1_t1 ~ attnic_t1 0.000 0.000 0.000 0.000 0.000
27 attnic_t1 ~~ attnic_t1 0.000 0.000 0.000 0.000 0.000
35 knovap_t1 ~1 0.000 0.000 0.000 0.000 0.000
61 attnic_t1 ~ rsk1_t1 0.000 0.000 0.000 0.000 0.000
36 attnic_t1 ~1 0.000 0.000 0.000 0.000 0.000
34 rsk1_t1 ~1 0.000 0.000 0.000 0.000 0.000
23 rsk1_t1 ~~ knovap_t1 0.000 0.000 0.000 NA 0.000
49 rsk1_t1 ~ knovap_t1 0.000 0.000 0.000 0.000 0.000EToH_Indirect <- '
## Latent Variables ##
# POS_coping_t1 =~ cope2_t1 + cope5_t1 + cope7_t1
# POS_coping_t2 =~ cope2_t2 + cope5_t2 + cope7_t2
# Neg_coping_t1 =~ cope1_t1 + cope3_t1 + cope4_t1
#Neg_coping_t2 =~ cope1_t2 + cope3_t2 + cope4_t2
Refusal_t1 =~ rsvap1_t1 + rsvap2_t1 + rsvap3_t1 + rsvap4_t1 + rsvap5_t1
Refusal_t2 =~ rsvap1_t2 + rsvap2_t2 + rsvap3_t2 + rsvap4_t2 + rsvap5_t2
# Time 1 covariances
#rsvap1_t1 ~~ rsvap2_t1
#rsvap1_t1 ~~ rsvap3_t1
rsvap1_t1 ~~ rsvap4_t1
#rsvap1_t1 ~~ rsvap5_t1
#rsvap2_t1 ~~ rsvap3_t1
#rsvap2_t1 ~~ rsvap4_t1
rsvap2_t1 ~~ rsvap5_t1
#rsvap3_t1 ~~ rsvap4_t1
rsvap3_t1 ~~ rsvap5_t1
#rsvap4_t1 ~~ rsvap5_t1
# Time 2 covariances
#rsvap1_t2 ~~ rsvap2_t2
#rsvap1_t2 ~~ rsvap3_t2
rsvap1_t2 ~~ rsvap4_t2
#rsvap1_t2 ~~ rsvap5_t2
#rsvap2_t2 ~~ rsvap3_t2
#rsvap2_t2 ~~ rsvap4_t2
rsvap2_t2 ~~ rsvap5_t2
#rsvap3_t2 ~~ rsvap4_t2
rsvap3_t2 ~~ rsvap5_t2
#rsvap4_t2 ~~ rsvap5_t2
## Regressions ##
usevap1_t2 ~ a*usevap1_t1 + b*rsk1_t2 + c*knovap_t2 + d*Refusal_t2 + e*attnic_t2 + t*rapd
'
Vaping_Indirect_Fit <- sem(Vaping_Indirect, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",
mimic = "Mplus",
)
summary(Vaping_Indirect_Fit, fit.measures = TRUE, standardized = TRUE)lavaan 0.6-19 ended normally after 71 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 45
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 306.519 244.793
Degrees of freedom 87 87
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.252
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2193.504 1486.989
Degrees of freedom 110 110
P-value 0.000 0.000
Scaling correction factor 1.475
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.895 0.885
Tucker-Lewis Index (TLI) 0.867 0.855
Robust Comparative Fit Index (CFI) 0.906
Robust Tucker-Lewis Index (TLI) 0.881
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3660.597 -3660.597
Scaling correction factor 1.843
for the MLR correction
Loglikelihood unrestricted model (H1) -3507.338 -3507.338
Scaling correction factor 1.454
for the MLR correction
Akaike (AIC) 7411.194 7411.194
Bayesian (BIC) 7578.312 7578.312
Sample-size adjusted Bayesian (SABIC) 7435.595 7435.595
Root Mean Square Error of Approximation:
RMSEA 0.091 0.077
90 Percent confidence interval - lower 0.080 0.067
90 Percent confidence interval - upper 0.102 0.088
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.954 0.346
Robust RMSEA 0.085
90 Percent confidence interval - lower 0.072
90 Percent confidence interval - upper 0.099
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.757
Standardized Root Mean Square Residual:
SRMR 0.106 0.106
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
Refusal_t1 =~
rsvap1_t1 1.000 0.683 0.736
rsvap2_t1 1.111 0.129 8.634 0.000 0.759 0.672
rsvap3_t1 1.365 0.144 9.489 0.000 0.932 0.901
rsvap4_t1 0.922 0.055 16.855 0.000 0.630 0.692
rsvap5_t1 1.004 0.148 6.783 0.000 0.686 0.597
Refusal_t2 =~
rsvap1_t2 1.000 0.614 0.713
rsvap2_t2 1.357 0.167 8.137 0.000 0.833 0.794
rsvap3_t2 1.295 0.175 7.401 0.000 0.795 0.810
rsvap4_t2 1.025 0.086 11.941 0.000 0.629 0.674
rsvap5_t2 1.219 0.180 6.780 0.000 0.748 0.703
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
usevap1_t2 ~
usevap1_t1 (a) -0.040 0.027 -1.496 0.135 -0.040 -0.069
rsk1_t2 (b) -0.061 0.069 -0.888 0.374 -0.061 -0.063
knovap_t2 (c) -0.235 0.296 -0.794 0.427 -0.235 -0.064
Refusal_t2 (d) -0.254 0.089 -2.845 0.004 -0.156 -0.238
attnic_t2 (e) -0.047 0.056 -0.837 0.403 -0.047 -0.067
rapd (t) -0.394 0.295 -1.333 0.182 -0.394 -0.112
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 ~~
.rsvap4_t1 0.277 0.058 4.741 0.000 0.277 0.672
.rsvap2_t1 ~~
.rsvap5_t1 0.253 0.071 3.545 0.000 0.253 0.328
.rsvap3_t1 ~~
.rsvap5_t1 0.088 0.048 1.821 0.069 0.088 0.212
.rsvap1_t2 ~~
.rsvap4_t2 0.271 0.056 4.826 0.000 0.271 0.652
.rsvap2_t2 ~~
.rsvap5_t2 0.124 0.068 1.832 0.067 0.124 0.257
.rsvap3_t2 ~~
.rsvap5_t2 0.097 0.063 1.536 0.124 0.097 0.224
Refusal_t1 ~~
Refusal_t2 0.229 0.049 4.694 0.000 0.547 0.547
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 3.442 0.053 64.592 0.000 3.442 3.711
.rsvap2_t1 2.974 0.065 45.872 0.000 2.974 2.635
.rsvap3_t1 3.122 0.059 52.516 0.000 3.122 3.017
.rsvap4_t1 3.439 0.052 65.820 0.000 3.439 3.781
.rsvap5_t1 2.954 0.066 44.786 0.000 2.954 2.572
.rsvap1_t2 3.432 0.049 69.432 0.000 3.432 3.989
.rsvap2_t2 3.145 0.060 52.176 0.000 3.145 2.997
.rsvap3_t2 3.267 0.056 58.000 0.000 3.267 3.332
.rsvap4_t2 3.426 0.054 63.875 0.000 3.426 3.670
.rsvap5_t2 3.155 0.061 51.566 0.000 3.155 2.964
.usevap1_t2 1.169 0.484 2.416 0.016 1.169 1.782
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsvap1_t1 0.394 0.062 6.396 0.000 0.394 0.458
.rsvap2_t1 0.697 0.091 7.623 0.000 0.697 0.548
.rsvap3_t1 0.202 0.057 3.521 0.000 0.202 0.189
.rsvap4_t1 0.431 0.059 7.360 0.000 0.431 0.521
.rsvap5_t1 0.849 0.098 8.688 0.000 0.849 0.644
.rsvap1_t2 0.364 0.058 6.248 0.000 0.364 0.491
.rsvap2_t2 0.407 0.074 5.483 0.000 0.407 0.370
.rsvap3_t2 0.330 0.065 5.103 0.000 0.330 0.343
.rsvap4_t2 0.476 0.068 7.016 0.000 0.476 0.546
.rsvap5_t2 0.573 0.101 5.656 0.000 0.573 0.506
.usevap1_t2 0.391 0.086 4.547 0.000 0.391 0.907
Refusal_t1 0.466 0.096 4.868 0.000 1.000 1.000
Refusal_t2 0.377 0.085 4.454 0.000 1.000 1.000Alc_Indirect <- '
## Latent Variables ##
Refusal_t1 =~ rsalc1_t1 + rsalc2_t1 + rsalc3_t1 + rsalc4_t1 + rsalc5_t1
Refusal_t2 =~ rsalc1_t2 + rsalc2_t2 + rsalc3_t2 + rsalc4_t2 + rsalc5_t2
# Time 1 covariances
#rsvap1_t1 ~~ rsvap2_t1
#rsvap1_t1 ~~ rsvap3_t1
rsalc1_t1 ~~ rsalc4_t1
#rsvap1_t1 ~~ rsvap5_t1
#rsvap2_t1 ~~ rsvap3_t1
#rsvap2_t1 ~~ rsvap4_t1
rsalc2_t1 ~~ rsalc5_t1
#rsvap3_t1 ~~ rsvap4_t1
rsalc3_t1 ~~ rsalc5_t1
#rsvap4_t1 ~~ rsvap5_t1
# Time 2 covariances
#rsvap1_t2 ~~ rsvap2_t2
#rsvap1_t2 ~~ rsvap3_t2
rsalc1_t2 ~~ rsalc4_t2
#rsvap1_t2 ~~ rsalc5_t2
#rsvap2_t2 ~~ rsvap3_t2
#rsvap2_t2 ~~ rsvap4_t2
rsalc2_t2 ~~ rsalc5_t2
#rsvap3_t2 ~~ rsvap4_t2
rsalc3_t2 ~~ rsalc5_t2
#rsvap4_t2 ~~ rsvap5_t2
## Regressions ##
usealc1_t2 ~ a*usealc1_t1 + b*rsk1_t2 + d*Refusal_t2 + e*attalc_t2 + t*rapd
Refusal_t2 ~ rapd
'
Alc_Indirect_Fit <- sem(Alc_Indirect, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",
mimic = "Mplus",
)
summary(Alc_Indirect_Fit, fit.measures = TRUE, standardized = TRUE)lavaan 0.6-19 ended normally after 70 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 44
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 304.025 233.413
Degrees of freedom 77 77
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.303
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2452.863 1567.482
Degrees of freedom 99 99
P-value 0.000 0.000
Scaling correction factor 1.565
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.904 0.893
Tucker-Lewis Index (TLI) 0.876 0.863
Robust Comparative Fit Index (CFI) 0.914
Robust Tucker-Lewis Index (TLI) 0.889
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3431.689 -3431.689
Scaling correction factor 1.960
for the MLR correction
Loglikelihood unrestricted model (H1) -3279.677 -3279.677
Scaling correction factor 1.542
for the MLR correction
Akaike (AIC) 6951.379 6951.379
Bayesian (BIC) 7114.783 7114.783
Sample-size adjusted Bayesian (SABIC) 6975.238 6975.238
Root Mean Square Error of Approximation:
RMSEA 0.099 0.082
90 Percent confidence interval - lower 0.087 0.071
90 Percent confidence interval - upper 0.110 0.092
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 0.996 0.626
Robust RMSEA 0.092
90 Percent confidence interval - lower 0.079
90 Percent confidence interval - upper 0.107
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.930
Standardized Root Mean Square Residual:
SRMR 0.182 0.182
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
Refusal_t1 =~
rsalc1_t1 1.000 0.683 0.753
rsalc2_t1 1.168 0.132 8.827 0.000 0.798 0.711
rsalc3_t1 1.401 0.150 9.309 0.000 0.957 0.922
rsalc4_t1 0.992 0.051 19.320 0.000 0.677 0.746
rsalc5_t1 1.137 0.134 8.479 0.000 0.776 0.683
Refusal_t2 =~
rsalc1_t2 1.000 0.558 0.708
rsalc2_t2 1.416 0.186 7.613 0.000 0.790 0.798
rsalc3_t2 1.482 0.184 8.059 0.000 0.826 0.880
rsalc4_t2 1.085 0.098 11.017 0.000 0.605 0.653
rsalc5_t2 1.365 0.201 6.779 0.000 0.761 0.756
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
usealc1_t2 ~
usealc1_t1 (a) 0.086 0.042 2.035 0.042 0.086 0.105
rsk1_t2 (b) -0.051 0.074 -0.689 0.491 -0.051 -0.054
Refusal_t2 (d) -0.168 0.076 -2.226 0.026 -0.094 -0.146
attalc_t2 (e) -0.010 0.043 -0.234 0.815 -0.010 -0.015
rapd (t) -0.593 0.328 -1.806 0.071 -0.593 -0.173
Refusal_t2 ~
rapd 0.590 0.281 2.103 0.035 1.058 0.198
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsalc1_t1 ~~
.rsalc4_t1 0.246 0.053 4.627 0.000 0.246 0.680
.rsalc2_t1 ~~
.rsalc5_t1 0.197 0.060 3.278 0.001 0.197 0.301
.rsalc3_t1 ~~
.rsalc5_t1 0.176 0.054 3.230 0.001 0.176 0.526
.rsalc1_t2 ~~
.rsalc4_t2 0.241 0.051 4.685 0.000 0.241 0.618
.rsalc2_t2 ~~
.rsalc5_t2 0.121 0.063 1.914 0.056 0.121 0.308
.rsalc3_t2 ~~
.rsalc5_t2 0.088 0.050 1.778 0.075 0.088 0.301
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsalc1_t1 3.469 0.052 66.544 0.000 3.469 3.823
.rsalc2_t1 3.086 0.064 47.853 0.000 3.086 2.749
.rsalc3_t1 3.221 0.060 54.040 0.000 3.221 3.105
.rsalc4_t1 3.482 0.052 66.771 0.000 3.482 3.836
.rsalc5_t1 3.056 0.065 46.767 0.000 3.056 2.687
.rsalc1_t2 2.950 0.285 10.352 0.000 2.950 3.748
.rsalc2_t2 2.409 0.360 6.685 0.000 2.409 2.433
.rsalc3_t2 2.511 0.375 6.688 0.000 2.511 2.674
.rsalc4_t2 2.809 0.305 9.222 0.000 2.809 3.032
.rsalc5_t2 2.478 0.336 7.380 0.000 2.478 2.462
.usealc1_t2 0.957 0.415 2.308 0.021 0.957 1.493
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsalc1_t1 0.357 0.058 6.195 0.000 0.357 0.433
.rsalc2_t1 0.623 0.097 6.438 0.000 0.623 0.495
.rsalc3_t1 0.162 0.059 2.729 0.006 0.162 0.150
.rsalc4_t1 0.365 0.058 6.287 0.000 0.365 0.443
.rsalc5_t1 0.691 0.095 7.289 0.000 0.691 0.534
.rsalc1_t2 0.308 0.050 6.139 0.000 0.308 0.498
.rsalc2_t2 0.357 0.070 5.113 0.000 0.357 0.364
.rsalc3_t2 0.199 0.047 4.212 0.000 0.199 0.226
.rsalc4_t2 0.493 0.073 6.748 0.000 0.493 0.574
.rsalc5_t2 0.434 0.087 4.983 0.000 0.434 0.428
.usealc1_t2 0.376 0.085 4.399 0.000 0.376 0.916
Refusal_t1 0.466 0.096 4.836 0.000 1.000 1.000
.Refusal_t2 0.299 0.069 4.347 0.000 0.961 0.961MJ_Indirect <- '
## Latent Variables ##
Refusal_t1 =~ rsmj1_t1 + rsmj2_t1 + rsmj3_t1 + rsmj4_t1 + rsmj5_t1
Refusal_t2 =~ rsmj1_t2 + rsmj2_t2 + rsmj3_t2 + rsmj4_t2 + rsmj5_t2
# Time 1 covariances
#rsvap1_t1 ~~ rsvap2_t1
#rsvap1_t1 ~~ rsvap3_t1
rsmj1_t1 ~~ rsmj4_t1
#rsvap1_t1 ~~ rsvap5_t1
#rsvap2_t1 ~~ rsvap3_t1
#rsvap2_t1 ~~ rsvap4_t1
rsmj2_t1 ~~ rsmj5_t1
#rsvap3_t1 ~~ rsvap4_t1
rsmj3_t1 ~~ rsmj5_t1
#rsvap4_t1 ~~ rsvap5_t1
# Time 2 covariances
#rsvap1_t2 ~~ rsvap2_t2
#rsvap1_t2 ~~ rsvap3_t2
rsmj1_t2 ~~ rsmj4_t2
#rsvap1_t2 ~~ rsalc5_t2
#rsvap2_t2 ~~ rsvap3_t2
#rsvap2_t2 ~~ rsvap4_t2
rsmj2_t2 ~~ rsmj5_t2
#rsvap3_t2 ~~ rsvap4_t2
rsmj3_t2 ~~ rsmj5_t2
#rsvap4_t2 ~~ rsvap5_t2
## Regressions ##
usemj1_t2 ~ a*usemj1_t1 + b*rsk1_t2 + d*Refusal_t2 + e*attmj_t2 + t*rapd
Refusal_t2 ~ rapd
'
MJ_Indirect_Fit <- sem(MJ_Indirect, data = Student_Data_Full_No_NA, estimator = "MLR",
sampling.weights = "ipw",
mimic = "Mplus",
)
summary(MJ_Indirect_Fit, fit.measures = TRUE, standardized = TRUE)lavaan 0.6-19 ended normally after 63 iterations
Estimator ML
Optimization method NLMINB
Number of model parameters 44
Number of observations 303
Number of missing patterns 1
Sampling weights variable ipw
Model Test User Model:
Standard Scaled
Test Statistic 331.845 249.445
Degrees of freedom 77 77
P-value (Chi-square) 0.000 0.000
Scaling correction factor 1.330
Yuan-Bentler correction (Mplus variant)
Model Test Baseline Model:
Test statistic 2297.703 1480.969
Degrees of freedom 99 99
P-value 0.000 0.000
Scaling correction factor 1.551
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.884 0.875
Tucker-Lewis Index (TLI) 0.851 0.840
Robust Comparative Fit Index (CFI) 0.895
Robust Tucker-Lewis Index (TLI) 0.865
Loglikelihood and Information Criteria:
Loglikelihood user model (H0) -3636.076 -3636.076
Scaling correction factor 1.855
for the MLR correction
Loglikelihood unrestricted model (H1) -3470.153 -3470.153
Scaling correction factor 1.521
for the MLR correction
Akaike (AIC) 7360.151 7360.151
Bayesian (BIC) 7523.556 7523.556
Sample-size adjusted Bayesian (SABIC) 7384.011 7384.011
Root Mean Square Error of Approximation:
RMSEA 0.105 0.086
90 Percent confidence interval - lower 0.093 0.076
90 Percent confidence interval - upper 0.116 0.096
P-value H_0: RMSEA <= 0.050 0.000 0.000
P-value H_0: RMSEA >= 0.080 1.000 0.835
Robust RMSEA 0.098
90 Percent confidence interval - lower 0.084
90 Percent confidence interval - upper 0.113
P-value H_0: Robust RMSEA <= 0.050 0.000
P-value H_0: Robust RMSEA >= 0.080 0.985
Standardized Root Mean Square Residual:
SRMR 0.190 0.190
Parameter Estimates:
Standard errors Sandwich
Information bread Observed
Observed information based on Hessian
Latent Variables:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
Refusal_t1 =~
rsmj1_t1 1.000 0.701 0.748
rsmj2_t1 1.079 0.119 9.089 0.000 0.757 0.680
rsmj3_t1 1.400 0.156 8.957 0.000 0.982 0.933
rsmj4_t1 0.998 0.061 16.265 0.000 0.700 0.729
rsmj5_t1 1.137 0.142 7.999 0.000 0.798 0.683
Refusal_t2 =~
rsmj1_t2 1.000 0.645 0.726
rsmj2_t2 1.284 0.138 9.307 0.000 0.829 0.813
rsmj3_t2 1.318 0.156 8.474 0.000 0.851 0.874
rsmj4_t2 0.981 0.099 9.919 0.000 0.633 0.679
rsmj5_t2 1.229 0.151 8.168 0.000 0.793 0.744
Regressions:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
usemj1_t2 ~
usemj1_t1 (a) 0.042 0.039 1.076 0.282 0.042 0.062
rsk1_t2 (b) -0.116 0.080 -1.448 0.147 -0.116 -0.122
Refusal_t2 (d) -0.174 0.075 -2.334 0.020 -0.112 -0.176
attmj_t2 (e) -0.027 0.052 -0.514 0.607 -0.027 -0.042
rapd (t) -0.344 0.293 -1.173 0.241 -0.344 -0.101
Refusal_t2 ~
rapd 0.754 0.253 2.976 0.003 1.168 0.219
Covariances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsmj1_t1 ~~
.rsmj4_t1 0.244 0.057 4.265 0.000 0.244 0.598
.rsmj2_t1 ~~
.rsmj5_t1 0.216 0.067 3.220 0.001 0.216 0.310
.rsmj3_t1 ~~
.rsmj5_t1 0.089 0.049 1.808 0.071 0.089 0.274
.rsmj1_t2 ~~
.rsmj4_t2 0.154 0.050 3.104 0.002 0.154 0.368
.rsmj2_t2 ~~
.rsmj5_t2 0.177 0.060 2.947 0.003 0.177 0.419
.rsmj3_t2 ~~
.rsmj5_t2 0.116 0.053 2.164 0.030 0.116 0.342
Intercepts:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsmj1_t1 3.426 0.054 63.634 0.000 3.426 3.656
.rsmj2_t1 3.056 0.064 47.752 0.000 3.056 2.743
.rsmj3_t1 3.165 0.060 52.337 0.000 3.165 3.007
.rsmj4_t1 3.413 0.055 61.856 0.000 3.413 3.554
.rsmj5_t1 2.977 0.067 44.393 0.000 2.977 2.550
.rsmj1_t2 2.745 0.260 10.572 0.000 2.745 3.088
.rsmj2_t2 2.278 0.287 7.935 0.000 2.278 2.236
.rsmj3_t2 2.309 0.318 7.258 0.000 2.309 2.371
.rsmj4_t2 2.746 0.264 10.383 0.000 2.746 2.946
.rsmj5_t2 2.301 0.303 7.596 0.000 2.301 2.157
.usemj1_t2 1.001 0.390 2.563 0.010 1.001 1.569
Variances:
Estimate Std.Err z-value P(>|z|) Std.lv Std.all
.rsmj1_t1 0.386 0.061 6.374 0.000 0.386 0.440
.rsmj2_t1 0.668 0.095 7.014 0.000 0.668 0.538
.rsmj3_t1 0.144 0.055 2.622 0.009 0.144 0.130
.rsmj4_t1 0.433 0.070 6.200 0.000 0.433 0.469
.rsmj5_t1 0.726 0.097 7.486 0.000 0.726 0.533
.rsmj1_t2 0.374 0.060 6.181 0.000 0.374 0.473
.rsmj2_t2 0.351 0.071 4.943 0.000 0.351 0.338
.rsmj3_t2 0.224 0.055 4.094 0.000 0.224 0.237
.rsmj4_t2 0.468 0.068 6.862 0.000 0.468 0.539
.rsmj5_t2 0.509 0.083 6.141 0.000 0.509 0.447
.usemj1_t2 0.372 0.086 4.311 0.000 0.372 0.915
Refusal_t1 0.492 0.103 4.795 0.000 1.000 1.000
.Refusal_t2 0.397 0.083 4.789 0.000 0.952 0.952