#------------ setwd
setwd("C:/Users/C00252837/Dropbox/StudentParentsData")
#------------Read in Data
data<-read.csv("sutdentparents_survey_weighted.csv", header = T)
data<-as_tibble(data)
names(data)## [1] "ï..Column1" "x1"
## [3] "Ã.Column1" "x"
## [5] "classification" "enrollment"
## [7] "department" "q4"
## [9] "finanacial_assistance" "q24_8_text"
## [11] "q23" "q38"
## [13] "q5" "q43"
## [15] "employment_status" "gender"
## [17] "gender2" "q10_5_text"
## [19] "age_original" "race"
## [21] "race2" "q46"
## [23] "q46_4_text" "q47"
## [25] "q47_11_text" "pregnancy"
## [27] "parenthood" "numb_children"
## [29] "age_children" "q35_13"
## [31] "q35_14" "q35_15"
## [33] "q62" "column226"
## [35] "res_aware_both_mean" "res_aware_patuniq_mean"
## [37] "res_use_both_mean" "res_use_patuniq_mean"
## [39] "socialsupport_both_mean" "socialsupport_patuniq_mean"
## [41] "positive_exp_both_mean" "positive_exp_patuniq_mean"
## [43] "negative_exp_gen_both_mean" "negative_exp_gen_patuniq_mean"
## [45] "academic_diffty_both_mean" "academic_diffty_patuniq_mean"
## [47] "financial_ins_both_mean" "financial_ins_patuniq_mean"
## [49] "housing_ins_both_mean" "physical_health_both_mean"
## [51] "psycsocemo_health_both_mean" "psycsocemo_health_patuniq_mean"
## [53] "expectations_both_mean" "expectations_patuniq_mean"
## [55] "pat_childcare_patuniq_mean" "child_issues_patuniq_mean"
## [57] "pregnancy_patuniq_mean" "age_recoded"
## [59] "age_recoded_narm" "parenthood_age"
## [61] "parenthood_age_narm" "res_aware_both_mean_recode"
## [63] "res_use_both_mean_recode" "socialsupport_both_mean_recode"
## [65] "positive_exp_both_mean_recode" "negative_exp_gen_both_mean_recod"
## [67] "academic_diffty_both_mean_recode" "financial_ins_both_mean_recode"
## [69] "housing_ins_both_mean_recode" "physical_health_both_mean_recode"
## [71] "psycsocemo_health_both_mean_reco" "nurs_or_not"
## [73] "age" "agegroup"
## [75] "binary_gender_original" "binary_gender"
## [77] "race3" "graduate"
## [79] "agegroup_tot" "binary_gender_tot"
## [81] "race3_tot" "graduate_tot"
## [83] "counter1" "sample_tot"
## [85] "baseweight" "finalweight"data <- data%>%
rename(
ID = x)#Total count of the sample (N=738)
count(data)## # A tibble: 1 x 1
## n
## <int>
## 1 738#parenthood status
table(data$parenthood)##
## No Yes
## 571 167prop.table(table(data$parenthood))##
## No Yes
## 0.7737127 0.2262873#graduate status
table(data$graduate)#0=undergraduate, 1=graduate##
## 0 1
## 535 203prop.table(table(data$graduate))##
## 0 1
## 0.7249322 0.2750678#parenthood by graduate status
table(data$parenthood, data$graduate)##
## 0 1
## No 445 126
## Yes 90 77prop.table(table(data$parenthood, data$graduate), margin=2)##
## 0 1
## No 0.8317757 0.6206897
## Yes 0.1682243 0.3793103#employment status
table(data$employment_status)##
## Full-time I do not work. Part-time
## 3 215 203 317prop.table(table(data$employment_status))##
## Full-time I do not work. Part-time
## 0.004065041 0.291327913 0.275067751 0.429539295#age groups
table(data$agegroup)##
## 1 2 3 4
## 134 200 115 289prop.table(table(data$agegroup))##
## 1 2 3 4
## 0.1815718 0.2710027 0.1558266 0.3915989#pregnancy
table(data$pregnancy)##
## No Yes
## 2 727 9prop.table(table(data$pregnancy))##
## No Yes
## 0.002710027 0.985094851 0.012195122library(survey)
des<-svydesign(ids=~1, weights=~finalweight, data = data)
#re-do the analysis from above using sample weights
library(questionr)
wtd.table(data$parenthood,weights = data$finalweight)#parenthood status## No Yes
## 12521 2203prop.table(wtd.table(data$parenthood,weights = data$finalweight))## No Yes
## 0.8503803 0.1496197wtd.table(data$graduate, weights = data$finalweight)#0=undergraduate, 1=graduate## 0 1
## 12353 2371prop.table(wtd.table(data$graduate, weights = data$finalweight))## 0 1
## 0.8389704 0.1610296wtd.table(data$parenthood, data$graduate, weights = data$finalweight)#parenthood by graduate status## 0 1
## No 10949 1572
## Yes 1404 799prop.table(wtd.table(data$parenthood, data$graduate, weights = data$finalweight), margin=2)## 0 1
## No 0.8863434 0.6630114
## Yes 0.1136566 0.3369886#employment status
wtd.table(data$employment_status, weights = data$finalweight)## Full-time I do not work. Part-time
## 73 3150 4492 7009prop.table(wtd.table(data$employment_status, weights = data$finalweight))## Full-time I do not work. Part-time
## 0.004957892 0.213936430 0.305080141 0.476025537#race3
##race3=0(Other),race3=1(Asian),race3=2(Black or African American),race3=3(Hispanic or Latino or Spanish origin of any race),race3=4 (White or Caucasian)
wtd.table(data$race3, weights = data$finalweight)#race3=0(Other),race3=1(Asian),race3=2(Black or African American),race3=3(Hispanic or Latino or Spanish origin of any race),race3=4 (White or Caucasian)## 0 1 2 3 4
## 1342 426 2938 852 9166prop.table(wtd.table(data$race3, weights = data$finalweight))## 0 1 2 3 4
## 0.09114371 0.02893236 0.19953817 0.05786471 0.62252105#age
#agegroup=1(age<20), agegroup=2(age>=20 & age<22),agegroup=3 (age>=22 & age<25),agegroup=4 (age>=25 & age!=.
wtd.table(data$agegroup, weights = data$finalweight)## 1 2 3 4
## 4123 4096 3003 3502prop.table(wtd.table(data$agegroup, weights = data$finalweight))## 1 2 3 4
## 0.2800190 0.2781853 0.2039527 0.2378430#Gender
#binary_gender=1 (Female),binary_gender=2 (Male)
wtd.table(data$binary_gender, weights = data$finalweight)## 1 2
## 8461 6263prop.table(wtd.table(data$binary_gender, weights = data$finalweight))## 1 2
## 0.57464 0.42536#pregnancy
wtd.table(data$pregnancy, weights = data$finalweight)## No Yes
## 27 14571 126prop.table(wtd.table(data$pregnancy, weights = data$finalweight))## No Yes
## 0.001833741 0.989608802 0.008557457data$parenthood<-as.factor(data$parenthood)
data$agegroup<-as.factor(data$agegroup)
data$binary_gender<-as.factor(data$binary_gender)#1=female, 2=male
data$race3<-as.factor(data$race3)
data$graduate<-as.factor(data$graduate)###################### academic_difficulty ##########################################################
#weighted
Hmisc::describe(data$academic_diffty_both_mean, weights = data$finalweight)## data$academic_diffty_both_mean
## n missing distinct Info Mean
## 11049 3675 5 0.897 3.381
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 70 1719 4545 3356 1359
## Proportion 0.006 0.156 0.411 0.304 0.123t.test(academic_diffty_both_mean~parenthood, data=data, weights = data$finalweight, var.equal=TRUE)##
## Two Sample t-test
##
## data: academic_diffty_both_mean by parenthood
## t = 3.0432, df = 540, p-value = 0.002454
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
## 0.1058207 0.4911664
## sample estimates:
## mean in group No mean in group Yes
## 3.381062 3.082569###################### psycsocemo_health_issues ##########################################################
#weighted
Hmisc::describe(data$psycsocemo_health_both_mean, weights = data$finalweight)## data$psycsocemo_health_both_mean
## n missing distinct Info Mean
## 11361 3363 5 0.888 3.592
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 42 1343 3469 4866 1641
## Proportion 0.004 0.118 0.305 0.428 0.144t.test(psycsocemo_health_both_mean~parenthood, data=data, weights = data$finalweight, var.equal=TRUE)##
## Two Sample t-test
##
## data: psycsocemo_health_both_mean by parenthood
## t = 2.4613, df = 555, p-value = 0.01415
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
## 0.04668813 0.41572232
## sample estimates:
## mean in group No mean in group Yes
## 3.621681 3.390476reg_psycsocemo_health_both<-lm(psycsocemo_health_both_mean~age + + binary_gender + race3 + graduate + parenthood + socialsupport_both_mean + financial_ins_both_mean + physical_health_both_mean+negative_exp_gen_both_mean+res_aware_both_mean+res_use_both_mean, data=data,weights = data$finalweight, var.equal=TRUE)
summary(reg_psycsocemo_health_both)##
## Call:
## lm(formula = psycsocemo_health_both_mean ~ age + +binary_gender +
## race3 + graduate + parenthood + socialsupport_both_mean +
## financial_ins_both_mean + physical_health_both_mean + negative_exp_gen_both_mean +
## res_aware_both_mean + res_use_both_mean, data = data, weights = data$finalweight,
## var.equal = TRUE)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -9.7646 -1.4429 0.1523 1.5828 10.8534
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.340462 0.305788 7.654 1.44e-13 ***
## age 0.009717 0.004898 1.984 0.047956 *
## binary_gender2 -0.031942 0.058456 -0.546 0.585069
## race31 -0.224753 0.194028 -1.158 0.247402
## race32 -0.312628 0.120877 -2.586 0.010048 *
## race33 0.110757 0.151485 0.731 0.465116
## race34 -0.177643 0.108040 -1.644 0.100904
## graduate1 -0.183319 0.089324 -2.052 0.040783 *
## parenthoodYes -0.153778 0.104915 -1.466 0.143496
## socialsupport_both_mean -0.194628 0.039873 -4.881 1.52e-06 ***
## financial_ins_both_mean 0.080372 0.040212 1.999 0.046309 *
## physical_health_both_mean 0.113511 0.031607 3.591 0.000369 ***
## negative_exp_gen_both_mean 0.351640 0.037877 9.284 < 2e-16 ***
## res_aware_both_mean -0.076619 0.034335 -2.232 0.026193 *
## res_use_both_mean 0.078480 0.049987 1.570 0.117193
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.584 on 405 degrees of freedom
## (318 observations deleted due to missingness)
## Multiple R-squared: 0.5598, Adjusted R-squared: 0.5446
## F-statistic: 36.79 on 14 and 405 DF, p-value: < 2.2e-16reg_psycsocemo_health_both<-lm(psycsocemo_health_both_mean~age + + binary_gender + race3 + graduate + parenthood + socialsupport_both_mean + financial_ins_both_mean + physical_health_both_mean+negative_exp_gen_both_mean+res_aware_both_mean+res_use_both_mean, data=data,weights = data$finalweight, var.equal=TRUE)
summary(reg_psycsocemo_health_both)##
## Call:
## lm(formula = psycsocemo_health_both_mean ~ age + +binary_gender +
## race3 + graduate + parenthood + socialsupport_both_mean +
## financial_ins_both_mean + physical_health_both_mean + negative_exp_gen_both_mean +
## res_aware_both_mean + res_use_both_mean, data = data, weights = data$finalweight,
## var.equal = TRUE)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -9.7646 -1.4429 0.1523 1.5828 10.8534
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.340462 0.305788 7.654 1.44e-13 ***
## age 0.009717 0.004898 1.984 0.047956 *
## binary_gender2 -0.031942 0.058456 -0.546 0.585069
## race31 -0.224753 0.194028 -1.158 0.247402
## race32 -0.312628 0.120877 -2.586 0.010048 *
## race33 0.110757 0.151485 0.731 0.465116
## race34 -0.177643 0.108040 -1.644 0.100904
## graduate1 -0.183319 0.089324 -2.052 0.040783 *
## parenthoodYes -0.153778 0.104915 -1.466 0.143496
## socialsupport_both_mean -0.194628 0.039873 -4.881 1.52e-06 ***
## financial_ins_both_mean 0.080372 0.040212 1.999 0.046309 *
## physical_health_both_mean 0.113511 0.031607 3.591 0.000369 ***
## negative_exp_gen_both_mean 0.351640 0.037877 9.284 < 2e-16 ***
## res_aware_both_mean -0.076619 0.034335 -2.232 0.026193 *
## res_use_both_mean 0.078480 0.049987 1.570 0.117193
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.584 on 405 degrees of freedom
## (318 observations deleted due to missingness)
## Multiple R-squared: 0.5598, Adjusted R-squared: 0.5446
## F-statistic: 36.79 on 14 and 405 DF, p-value: < 2.2e-16reg_academic_diffty_both_mean<-lm(academic_diffty_both_mean~age + binary_gender + race3 + graduate + parenthood + socialsupport_both_mean + financial_ins_both_mean + physical_health_both_mean + psycsocemo_health_both_mean +negative_exp_gen_both_mean+res_aware_both_mean+res_use_both_mean, data=data, weights = data$finalweight, var.equal=TRUE)
summary(reg_academic_diffty_both_mean)##
## Call:
## lm(formula = academic_diffty_both_mean ~ age + binary_gender +
## race3 + graduate + parenthood + socialsupport_both_mean +
## financial_ins_both_mean + physical_health_both_mean + psycsocemo_health_both_mean +
## negative_exp_gen_both_mean + res_aware_both_mean + res_use_both_mean,
## data = data, weights = data$finalweight, var.equal = TRUE)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -8.9572 -1.5377 0.0451 1.5860 8.3100
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.030413 0.337804 3.050 0.002445 **
## age 0.003766 0.005134 0.734 0.463635
## binary_gender2 0.188868 0.059949 3.150 0.001758 **
## race31 -0.049806 0.197089 -0.253 0.800627
## race32 -0.244506 0.127229 -1.922 0.055374 .
## race33 -0.068956 0.160077 -0.431 0.666878
## race34 -0.347905 0.113466 -3.066 0.002322 **
## graduate1 -0.191759 0.092668 -2.069 0.039186 *
## parenthoodYes -0.027261 0.106857 -0.255 0.798766
## socialsupport_both_mean -0.038395 0.042218 -0.909 0.363687
## financial_ins_both_mean 0.277161 0.041316 6.708 7.07e-11 ***
## physical_health_both_mean -0.002769 0.032802 -0.084 0.932770
## psycsocemo_health_both_mean 0.179274 0.050813 3.528 0.000469 ***
## negative_exp_gen_both_mean 0.292907 0.042470 6.897 2.20e-11 ***
## res_aware_both_mean -0.089898 0.035379 -2.541 0.011446 *
## res_use_both_mean 0.102530 0.051325 1.998 0.046460 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.59 on 384 degrees of freedom
## (338 observations deleted due to missingness)
## Multiple R-squared: 0.5927, Adjusted R-squared: 0.5768
## F-statistic: 37.25 on 15 and 384 DF, p-value: < 2.2e-16#un-weighted (lots of missing values!)
Hmisc::describe(data$res_aware_patuniq_mean)## data$res_aware_patuniq_mean
## n missing distinct Info Mean Gmd
## 97 641 5 0.832 2.588 0.7981
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 4 43 42 5 3
## Proportion 0.041 0.443 0.433 0.052 0.031Hmisc::describe(data$res_use_patuniq_mean)## data$res_use_patuniq_mean
## n missing distinct Info Mean Gmd
## 47 691 4 0.668 3.319 0.5532
##
## Value 2 3 4 5
## Frequency 1 32 12 2
## Proportion 0.021 0.681 0.255 0.043Hmisc::describe(data$socialsupport_patuniq_mean)## data$socialsupport_patuniq_mean
## n missing distinct Info Mean Gmd
## 92 646 4 0.842 3.543 0.786
##
## Value 2 3 4 5
## Frequency 7 35 43 7
## Proportion 0.076 0.380 0.467 0.076Hmisc::describe(data$positive_exp_patuniq_mean)## data$positive_exp_patuniq_mean
## n missing distinct Info Mean Gmd
## 99 639 4 0.729 3.758 0.5797
##
## Value 2 3 4 5
## Frequency 1 29 62 7
## Proportion 0.010 0.293 0.626 0.071Hmisc::describe(data$negative_exp_gen_patuniq_mean)## data$negative_exp_gen_patuniq_mean
## n missing distinct Info Mean Gmd
## 99 639 4 0.729 3.758 0.5797
##
## Value 2 3 4 5
## Frequency 1 29 62 7
## Proportion 0.010 0.293 0.626 0.071Hmisc::describe(data$financial_ins_patuniq_mean)## data$financial_ins_patuniq_mean
## n missing distinct Info Mean Gmd
## 552 186 5 0.904 3.21 1.008
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 9 120 212 168 43
## Proportion 0.016 0.217 0.384 0.304 0.078Hmisc::describe(data$academic_diffty_patuniq_mean)## data$academic_diffty_patuniq_mean
## n missing distinct Info Mean Gmd
## 99 639 5 0.921 3.394 1.107
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 1 19 34 30 15
## Proportion 0.010 0.192 0.343 0.303 0.152Hmisc::describe(data$psycsocemo_health_patuniq_mean)## data$psycsocemo_health_patuniq_mean
## n missing distinct Info Mean Gmd
## 99 639 4 0.874 3.455 0.9
##
## Value 2 3 4 5
## Frequency 14 34 43 8
## Proportion 0.141 0.343 0.434 0.081Hmisc::describe(data$pat_childcare_patuniq_mean)## data$pat_childcare_patuniq_mean
## n missing distinct Info Mean Gmd
## 85 653 4 0.82 3.659 0.7092
##
## Value 2 3 4 5
## Frequency 2 33 42 8
## Proportion 0.024 0.388 0.494 0.094Hmisc::describe(data$child_issues_patuniq_mean)## data$child_issues_patuniq_mean
## n missing distinct Info Mean Gmd
## 74 664 4 0.871 3.554 0.8741
##
## Value 2 3 4 5
## Frequency 6 30 29 9
## Proportion 0.081 0.405 0.392 0.122Hmisc::describe(data$physical_health_both_mean)## data$physical_health_both_mean
## n missing distinct Info Mean Gmd
## 644 94 5 0.928 3.446 1.167
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 19 105 207 196 117
## Proportion 0.030 0.163 0.321 0.304 0.182#weighted (such missingness warrants cautious generalization!)
Hmisc::describe(data$res_aware_patuniq_mean, weights = data$finalweight)## data$res_aware_patuniq_mean
## n missing distinct Info Mean
## 1294 13430 5 0.833 2.65
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 48 517 606 86 37
## Proportion 0.037 0.400 0.468 0.066 0.029Hmisc::describe(data$res_use_patuniq_mean, weights = data$finalweight)## data$res_use_patuniq_mean
## n missing distinct Info Mean
## 723 14001 4 0.673 3.347
##
## Value 2 3 4 5
## Frequency 10 489 187 37
## Proportion 0.014 0.676 0.259 0.051Hmisc::describe(data$socialsupport_patuniq_mean, weights = data$finalweight)## data$socialsupport_patuniq_mean
## n missing distinct Info Mean
## 1236 13488 4 0.84 3.483
##
## Value 2 3 4 5
## Frequency 100 512 551 73
## Proportion 0.081 0.414 0.446 0.059Hmisc::describe(data$positive_exp_patuniq_mean, weights = data$finalweight)## data$positive_exp_patuniq_mean
## n missing distinct Info Mean
## 1345 13379 4 0.736 3.77
##
## Value 2 3 4 5
## Frequency 15 387 835 108
## Proportion 0.011 0.288 0.621 0.080Hmisc::describe(data$negative_exp_gen_patuniq_mean, weights = data$finalweight)## data$negative_exp_gen_patuniq_mean
## n missing distinct Info Mean
## 1345 13379 4 0.736 3.77
##
## Value 2 3 4 5
## Frequency 15 387 835 108
## Proportion 0.011 0.288 0.621 0.080Hmisc::describe(data$financial_ins_patuniq_mean, weights = data$finalweight)## data$financial_ins_patuniq_mean
## n missing distinct Info Mean
## 11179 3545 5 0.902 3.203
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 228 2337 4434 3300 880
## Proportion 0.020 0.209 0.397 0.295 0.079Hmisc::describe(data$academic_diffty_patuniq_mean, weights = data$finalweight)## data$academic_diffty_patuniq_mean
## n missing distinct Info Mean
## 1343 13381 5 0.927 3.336
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 10 319 420 398 196
## Proportion 0.007 0.238 0.313 0.296 0.146Hmisc::describe(data$psycsocemo_health_patuniq_mean, weights = data$finalweight)## data$psycsocemo_health_patuniq_mean
## n missing distinct Info Mean
## 1346 13378 4 0.871 3.526
##
## Value 2 3 4 5
## Frequency 177 419 615 135
## Proportion 0.132 0.311 0.457 0.100Hmisc::describe(data$pat_childcare_patuniq_mean, weights = data$finalweight)## data$pat_childcare_patuniq_mean
## n missing distinct Info Mean
## 1159 13565 4 0.822 3.632
##
## Value 2 3 4 5
## Frequency 20 495 536 108
## Proportion 0.017 0.427 0.462 0.093Hmisc::describe(data$child_issues_patuniq_mean, weights = data$finalweight)## data$child_issues_patuniq_mean
## n missing distinct Info Mean
## 1060 13664 4 0.872 3.552
##
## Value 2 3 4 5
## Frequency 91 420 422 127
## Proportion 0.086 0.396 0.398 0.120Hmisc::describe(data$physical_health_both_mean, weights = data$finalweight)## data$physical_health_both_mean
## n missing distinct Info Mean
## 12762 1962 5 0.93 3.376
##
## lowest : 1 2 3 4 5, highest: 1 2 3 4 5
##
## Value 1 2 3 4 5
## Frequency 464 2262 4160 3763 2113
## Proportion 0.036 0.177 0.326 0.295 0.166patuniq <- dplyr::select(data, res_aware_patuniq_mean, res_use_patuniq_mean, socialsupport_patuniq_mean, negative_exp_gen_patuniq_mean, academic_diffty_patuniq_mean, financial_ins_patuniq_mean, physical_health_both_mean, psycsocemo_health_patuniq_mean, pat_childcare_patuniq_mean, child_issues_patuniq_mean)
#pairwise deletion: [rcorr(as.matrix(patuniq), type="pearson")]
#The default of rcorr() is pairwise deletion. To do listwide deletion, remove incomplete data first.
patuniq_complete<-patuniq[complete.cases(patuniq),]
cor.matrix<-rcorr(as.matrix(patuniq_complete), type="pearson")
cor.matrix## res_aware_patuniq_mean res_use_patuniq_mean
## res_aware_patuniq_mean 1.00 0.28
## res_use_patuniq_mean 0.28 1.00
## socialsupport_patuniq_mean 0.34 0.29
## negative_exp_gen_patuniq_mean -0.01 0.47
## academic_diffty_patuniq_mean -0.10 0.14
## financial_ins_patuniq_mean 0.12 -0.11
## physical_health_both_mean 0.26 0.04
## psycsocemo_health_patuniq_mean 0.09 0.15
## pat_childcare_patuniq_mean 0.11 0.16
## child_issues_patuniq_mean 0.30 0.13
## socialsupport_patuniq_mean
## res_aware_patuniq_mean 0.34
## res_use_patuniq_mean 0.29
## socialsupport_patuniq_mean 1.00
## negative_exp_gen_patuniq_mean 0.22
## academic_diffty_patuniq_mean 0.19
## financial_ins_patuniq_mean 0.04
## physical_health_both_mean -0.04
## psycsocemo_health_patuniq_mean -0.01
## pat_childcare_patuniq_mean 0.13
## child_issues_patuniq_mean 0.26
## negative_exp_gen_patuniq_mean
## res_aware_patuniq_mean -0.01
## res_use_patuniq_mean 0.47
## socialsupport_patuniq_mean 0.22
## negative_exp_gen_patuniq_mean 1.00
## academic_diffty_patuniq_mean 0.09
## financial_ins_patuniq_mean -0.15
## physical_health_both_mean -0.05
## psycsocemo_health_patuniq_mean -0.16
## pat_childcare_patuniq_mean -0.07
## child_issues_patuniq_mean -0.20
## academic_diffty_patuniq_mean
## res_aware_patuniq_mean -0.10
## res_use_patuniq_mean 0.14
## socialsupport_patuniq_mean 0.19
## negative_exp_gen_patuniq_mean 0.09
## academic_diffty_patuniq_mean 1.00
## financial_ins_patuniq_mean 0.46
## physical_health_both_mean 0.12
## psycsocemo_health_patuniq_mean 0.49
## pat_childcare_patuniq_mean 0.62
## child_issues_patuniq_mean 0.49
## financial_ins_patuniq_mean
## res_aware_patuniq_mean 0.12
## res_use_patuniq_mean -0.11
## socialsupport_patuniq_mean 0.04
## negative_exp_gen_patuniq_mean -0.15
## academic_diffty_patuniq_mean 0.46
## financial_ins_patuniq_mean 1.00
## physical_health_both_mean 0.33
## psycsocemo_health_patuniq_mean 0.34
## pat_childcare_patuniq_mean 0.47
## child_issues_patuniq_mean 0.55
## physical_health_both_mean
## res_aware_patuniq_mean 0.26
## res_use_patuniq_mean 0.04
## socialsupport_patuniq_mean -0.04
## negative_exp_gen_patuniq_mean -0.05
## academic_diffty_patuniq_mean 0.12
## financial_ins_patuniq_mean 0.33
## physical_health_both_mean 1.00
## psycsocemo_health_patuniq_mean 0.41
## pat_childcare_patuniq_mean 0.17
## child_issues_patuniq_mean 0.36
## psycsocemo_health_patuniq_mean
## res_aware_patuniq_mean 0.09
## res_use_patuniq_mean 0.15
## socialsupport_patuniq_mean -0.01
## negative_exp_gen_patuniq_mean -0.16
## academic_diffty_patuniq_mean 0.49
## financial_ins_patuniq_mean 0.34
## physical_health_both_mean 0.41
## psycsocemo_health_patuniq_mean 1.00
## pat_childcare_patuniq_mean 0.73
## child_issues_patuniq_mean 0.52
## pat_childcare_patuniq_mean
## res_aware_patuniq_mean 0.11
## res_use_patuniq_mean 0.16
## socialsupport_patuniq_mean 0.13
## negative_exp_gen_patuniq_mean -0.07
## academic_diffty_patuniq_mean 0.62
## financial_ins_patuniq_mean 0.47
## physical_health_both_mean 0.17
## psycsocemo_health_patuniq_mean 0.73
## pat_childcare_patuniq_mean 1.00
## child_issues_patuniq_mean 0.65
## child_issues_patuniq_mean
## res_aware_patuniq_mean 0.30
## res_use_patuniq_mean 0.13
## socialsupport_patuniq_mean 0.26
## negative_exp_gen_patuniq_mean -0.20
## academic_diffty_patuniq_mean 0.49
## financial_ins_patuniq_mean 0.55
## physical_health_both_mean 0.36
## psycsocemo_health_patuniq_mean 0.52
## pat_childcare_patuniq_mean 0.65
## child_issues_patuniq_mean 1.00
##
## n= 39
##
##
## P
## res_aware_patuniq_mean res_use_patuniq_mean
## res_aware_patuniq_mean 0.0825
## res_use_patuniq_mean 0.0825
## socialsupport_patuniq_mean 0.0355 0.0703
## negative_exp_gen_patuniq_mean 0.9289 0.0027
## academic_diffty_patuniq_mean 0.5573 0.3874
## financial_ins_patuniq_mean 0.4833 0.5212
## physical_health_both_mean 0.1136 0.8106
## psycsocemo_health_patuniq_mean 0.5870 0.3683
## pat_childcare_patuniq_mean 0.5231 0.3181
## child_issues_patuniq_mean 0.0637 0.4475
## socialsupport_patuniq_mean
## res_aware_patuniq_mean 0.0355
## res_use_patuniq_mean 0.0703
## socialsupport_patuniq_mean
## negative_exp_gen_patuniq_mean 0.1691
## academic_diffty_patuniq_mean 0.2468
## financial_ins_patuniq_mean 0.8185
## physical_health_both_mean 0.8268
## psycsocemo_health_patuniq_mean 0.9340
## pat_childcare_patuniq_mean 0.4359
## child_issues_patuniq_mean 0.1170
## negative_exp_gen_patuniq_mean
## res_aware_patuniq_mean 0.9289
## res_use_patuniq_mean 0.0027
## socialsupport_patuniq_mean 0.1691
## negative_exp_gen_patuniq_mean
## academic_diffty_patuniq_mean 0.6041
## financial_ins_patuniq_mean 0.3495
## physical_health_both_mean 0.7466
## psycsocemo_health_patuniq_mean 0.3401
## pat_childcare_patuniq_mean 0.6682
## child_issues_patuniq_mean 0.2268
## academic_diffty_patuniq_mean
## res_aware_patuniq_mean 0.5573
## res_use_patuniq_mean 0.3874
## socialsupport_patuniq_mean 0.2468
## negative_exp_gen_patuniq_mean 0.6041
## academic_diffty_patuniq_mean
## financial_ins_patuniq_mean 0.0029
## physical_health_both_mean 0.4531
## psycsocemo_health_patuniq_mean 0.0015
## pat_childcare_patuniq_mean 0.0000
## child_issues_patuniq_mean 0.0016
## financial_ins_patuniq_mean
## res_aware_patuniq_mean 0.4833
## res_use_patuniq_mean 0.5212
## socialsupport_patuniq_mean 0.8185
## negative_exp_gen_patuniq_mean 0.3495
## academic_diffty_patuniq_mean 0.0029
## financial_ins_patuniq_mean
## physical_health_both_mean 0.0434
## psycsocemo_health_patuniq_mean 0.0370
## pat_childcare_patuniq_mean 0.0023
## child_issues_patuniq_mean 0.0003
## physical_health_both_mean
## res_aware_patuniq_mean 0.1136
## res_use_patuniq_mean 0.8106
## socialsupport_patuniq_mean 0.8268
## negative_exp_gen_patuniq_mean 0.7466
## academic_diffty_patuniq_mean 0.4531
## financial_ins_patuniq_mean 0.0434
## physical_health_both_mean
## psycsocemo_health_patuniq_mean 0.0104
## pat_childcare_patuniq_mean 0.3066
## child_issues_patuniq_mean 0.0237
## psycsocemo_health_patuniq_mean
## res_aware_patuniq_mean 0.5870
## res_use_patuniq_mean 0.3683
## socialsupport_patuniq_mean 0.9340
## negative_exp_gen_patuniq_mean 0.3401
## academic_diffty_patuniq_mean 0.0015
## financial_ins_patuniq_mean 0.0370
## physical_health_both_mean 0.0104
## psycsocemo_health_patuniq_mean
## pat_childcare_patuniq_mean 0.0000
## child_issues_patuniq_mean 0.0007
## pat_childcare_patuniq_mean
## res_aware_patuniq_mean 0.5231
## res_use_patuniq_mean 0.3181
## socialsupport_patuniq_mean 0.4359
## negative_exp_gen_patuniq_mean 0.6682
## academic_diffty_patuniq_mean 0.0000
## financial_ins_patuniq_mean 0.0023
## physical_health_both_mean 0.3066
## psycsocemo_health_patuniq_mean 0.0000
## pat_childcare_patuniq_mean
## child_issues_patuniq_mean 0.0000
## child_issues_patuniq_mean
## res_aware_patuniq_mean 0.0637
## res_use_patuniq_mean 0.4475
## socialsupport_patuniq_mean 0.1170
## negative_exp_gen_patuniq_mean 0.2268
## academic_diffty_patuniq_mean 0.0016
## financial_ins_patuniq_mean 0.0003
## physical_health_both_mean 0.0237
## psycsocemo_health_patuniq_mean 0.0007
## pat_childcare_patuniq_mean 0.0000
## child_issues_patuniq_mean##correlation coefficients(repetitive codes)
# r's
#cor_df_r<-as.data.frame.matrix(round(cor.matrix$r,2)) #round to 2 d.p.
#cor_df_r# p's
cor_df_p<-as.data.frame.matrix(round(cor.matrix$P,3)) #round to 3 d.p.
cor_df_p[cor_df_p == 0] <- "< .001"
cor_df_p[is.na(cor_df_p)] <- "-"
cor_df_p## res_aware_patuniq_mean res_use_patuniq_mean
## res_aware_patuniq_mean - 0.083
## res_use_patuniq_mean 0.083 -
## socialsupport_patuniq_mean 0.036 0.07
## negative_exp_gen_patuniq_mean 0.929 0.003
## academic_diffty_patuniq_mean 0.557 0.387
## financial_ins_patuniq_mean 0.483 0.521
## physical_health_both_mean 0.114 0.811
## psycsocemo_health_patuniq_mean 0.587 0.368
## pat_childcare_patuniq_mean 0.523 0.318
## child_issues_patuniq_mean 0.064 0.447
## socialsupport_patuniq_mean
## res_aware_patuniq_mean 0.036
## res_use_patuniq_mean 0.07
## socialsupport_patuniq_mean -
## negative_exp_gen_patuniq_mean 0.169
## academic_diffty_patuniq_mean 0.247
## financial_ins_patuniq_mean 0.818
## physical_health_both_mean 0.827
## psycsocemo_health_patuniq_mean 0.934
## pat_childcare_patuniq_mean 0.436
## child_issues_patuniq_mean 0.117
## negative_exp_gen_patuniq_mean
## res_aware_patuniq_mean 0.929
## res_use_patuniq_mean 0.003
## socialsupport_patuniq_mean 0.169
## negative_exp_gen_patuniq_mean -
## academic_diffty_patuniq_mean 0.604
## financial_ins_patuniq_mean 0.35
## physical_health_both_mean 0.747
## psycsocemo_health_patuniq_mean 0.34
## pat_childcare_patuniq_mean 0.668
## child_issues_patuniq_mean 0.227
## academic_diffty_patuniq_mean
## res_aware_patuniq_mean 0.557
## res_use_patuniq_mean 0.387
## socialsupport_patuniq_mean 0.247
## negative_exp_gen_patuniq_mean 0.604
## academic_diffty_patuniq_mean -
## financial_ins_patuniq_mean 0.003
## physical_health_both_mean 0.453
## psycsocemo_health_patuniq_mean 0.002
## pat_childcare_patuniq_mean < .001
## child_issues_patuniq_mean 0.002
## financial_ins_patuniq_mean
## res_aware_patuniq_mean 0.483
## res_use_patuniq_mean 0.521
## socialsupport_patuniq_mean 0.818
## negative_exp_gen_patuniq_mean 0.35
## academic_diffty_patuniq_mean 0.003
## financial_ins_patuniq_mean -
## physical_health_both_mean 0.043
## psycsocemo_health_patuniq_mean 0.037
## pat_childcare_patuniq_mean 0.002
## child_issues_patuniq_mean < .001
## physical_health_both_mean
## res_aware_patuniq_mean 0.114
## res_use_patuniq_mean 0.811
## socialsupport_patuniq_mean 0.827
## negative_exp_gen_patuniq_mean 0.747
## academic_diffty_patuniq_mean 0.453
## financial_ins_patuniq_mean 0.043
## physical_health_both_mean -
## psycsocemo_health_patuniq_mean 0.01
## pat_childcare_patuniq_mean 0.307
## child_issues_patuniq_mean 0.024
## psycsocemo_health_patuniq_mean
## res_aware_patuniq_mean 0.587
## res_use_patuniq_mean 0.368
## socialsupport_patuniq_mean 0.934
## negative_exp_gen_patuniq_mean 0.34
## academic_diffty_patuniq_mean 0.002
## financial_ins_patuniq_mean 0.037
## physical_health_both_mean 0.01
## psycsocemo_health_patuniq_mean -
## pat_childcare_patuniq_mean < .001
## child_issues_patuniq_mean 0.001
## pat_childcare_patuniq_mean
## res_aware_patuniq_mean 0.523
## res_use_patuniq_mean 0.318
## socialsupport_patuniq_mean 0.436
## negative_exp_gen_patuniq_mean 0.668
## academic_diffty_patuniq_mean < .001
## financial_ins_patuniq_mean 0.002
## physical_health_both_mean 0.307
## psycsocemo_health_patuniq_mean < .001
## pat_childcare_patuniq_mean -
## child_issues_patuniq_mean < .001
## child_issues_patuniq_mean
## res_aware_patuniq_mean 0.064
## res_use_patuniq_mean 0.447
## socialsupport_patuniq_mean 0.117
## negative_exp_gen_patuniq_mean 0.227
## academic_diffty_patuniq_mean 0.002
## financial_ins_patuniq_mean < .001
## physical_health_both_mean 0.024
## psycsocemo_health_patuniq_mean 0.001
## pat_childcare_patuniq_mean < .001
## child_issues_patuniq_mean -#un-weighted
reg_psycsocemo_health_patuniq_unweighted<-lm(psycsocemo_health_patuniq_mean~age + binary_gender + race3 + graduate + socialsupport_patuniq_mean + financial_ins_patuniq_mean + physical_health_both_mean+negative_exp_gen_patuniq_mean+res_aware_patuniq_mean+res_use_patuniq_mean +pat_childcare_patuniq_mean + child_issues_patuniq_mean, data=data,var.equal=TRUE)
summary(reg_psycsocemo_health_patuniq_unweighted)##
## Call:
## lm(formula = psycsocemo_health_patuniq_mean ~ age + binary_gender +
## race3 + graduate + socialsupport_patuniq_mean + financial_ins_patuniq_mean +
## physical_health_both_mean + negative_exp_gen_patuniq_mean +
## res_aware_patuniq_mean + res_use_patuniq_mean + pat_childcare_patuniq_mean +
## child_issues_patuniq_mean, data = data, var.equal = TRUE)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81443 -0.29390 -0.01053 0.21159 1.19739
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.320677 1.186640 1.113 0.276751
## age 0.008592 0.012972 0.662 0.514052
## binary_gender2 0.166571 0.215248 0.774 0.446571
## race31 0.772962 0.772913 1.000 0.327257
## race32 -0.009975 0.372237 -0.027 0.978844
## race33 0.784961 0.501852 1.564 0.130879
## race34 -0.181788 0.306904 -0.592 0.559171
## graduate1 -0.061275 0.199084 -0.308 0.760901
## socialsupport_patuniq_mean -0.076322 0.134288 -0.568 0.575080
## financial_ins_patuniq_mean -0.155445 0.130264 -1.193 0.244414
## physical_health_both_mean 0.167360 0.096245 1.739 0.094867 .
## negative_exp_gen_patuniq_mean -0.222797 0.176877 -1.260 0.219921
## res_aware_patuniq_mean -0.131226 0.150926 -0.869 0.393202
## res_use_patuniq_mean 0.150133 0.211184 0.711 0.483991
## pat_childcare_patuniq_mean 0.790396 0.173835 4.547 0.000131 ***
## child_issues_patuniq_mean -0.032063 0.196406 -0.163 0.871690
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5244 on 24 degrees of freedom
## (698 observations deleted due to missingness)
## Multiple R-squared: 0.7247, Adjusted R-squared: 0.5527
## F-statistic: 4.213 on 15 and 24 DF, p-value: 0.0008821#weighted
reg_psycsocemo_health_patuniq_weighted<-lm(psycsocemo_health_patuniq_mean~age + binary_gender + race3 + graduate + socialsupport_patuniq_mean + financial_ins_patuniq_mean + physical_health_both_mean+negative_exp_gen_patuniq_mean+res_aware_patuniq_mean+res_use_patuniq_mean + pat_childcare_patuniq_mean + child_issues_patuniq_mean, data=data,weights = data$finalweight, var.equal=TRUE)
summary(reg_psycsocemo_health_patuniq_weighted)##
## Call:
## lm(formula = psycsocemo_health_patuniq_mean ~ age + binary_gender +
## race3 + graduate + socialsupport_patuniq_mean + financial_ins_patuniq_mean +
## physical_health_both_mean + negative_exp_gen_patuniq_mean +
## res_aware_patuniq_mean + res_use_patuniq_mean + pat_childcare_patuniq_mean +
## child_issues_patuniq_mean, data = data, weights = data$finalweight,
## var.equal = TRUE)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -2.4743 -1.1633 -0.0809 0.8812 4.8336
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.094626 1.101760 0.086 0.9323
## age 0.009769 0.011384 0.858 0.3993
## binary_gender2 0.186021 0.213170 0.873 0.3915
## race31 0.437040 0.942738 0.464 0.6471
## race32 0.169979 0.321588 0.529 0.6020
## race33 0.968926 0.440013 2.202 0.0375 *
## race34 -0.229336 0.252422 -0.909 0.3726
## graduate1 0.080288 0.206894 0.388 0.7014
## socialsupport_patuniq_mean 0.067783 0.133678 0.507 0.6167
## financial_ins_patuniq_mean -0.259613 0.125133 -2.075 0.0489 *
## physical_health_both_mean 0.224053 0.096882 2.313 0.0296 *
## negative_exp_gen_patuniq_mean -0.074294 0.173542 -0.428 0.6724
## res_aware_patuniq_mean -0.160654 0.147761 -1.087 0.2877
## res_use_patuniq_mean 0.147217 0.244984 0.601 0.5535
## pat_childcare_patuniq_mean 0.870245 0.183561 4.741 8.02e-05 ***
## child_issues_patuniq_mean -0.041374 0.196284 -0.211 0.8348
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.955 on 24 degrees of freedom
## (698 observations deleted due to missingness)
## Multiple R-squared: 0.7577, Adjusted R-squared: 0.6063
## F-statistic: 5.004 on 15 and 24 DF, p-value: 0.0002464reg_academic_diffty_patuniq_unweighted<-lm(academic_diffty_patuniq_mean~
age + binary_gender + race3 + graduate +
socialsupport_patuniq_mean +
financial_ins_patuniq_mean +
physical_health_both_mean +
psycsocemo_health_patuniq_mean +
negative_exp_gen_patuniq_mean +
res_aware_patuniq_mean +
res_use_patuniq_mean +
pat_childcare_patuniq_mean +
child_issues_patuniq_mean,
data=data,var.equal=TRUE)
summary(reg_academic_diffty_patuniq_unweighted)##
## Call:
## lm(formula = academic_diffty_patuniq_mean ~ age + binary_gender +
## race3 + graduate + socialsupport_patuniq_mean + financial_ins_patuniq_mean +
## physical_health_both_mean + psycsocemo_health_patuniq_mean +
## negative_exp_gen_patuniq_mean + res_aware_patuniq_mean +
## res_use_patuniq_mean + pat_childcare_patuniq_mean + child_issues_patuniq_mean,
## data = data, var.equal = TRUE)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.68638 -0.32186 -0.01203 0.50568 1.49160
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.732536 2.175459 0.337 0.740
## age -0.022618 0.023087 -0.980 0.338
## binary_gender2 -0.323706 0.389084 -0.832 0.414
## race31 0.158215 1.404527 0.113 0.911
## race32 -0.816956 0.653910 -1.249 0.225
## race33 -0.390673 0.923042 -0.423 0.676
## race34 -0.663902 0.544890 -1.218 0.236
## graduate1 0.151955 0.359329 0.423 0.676
## socialsupport_patuniq_mean 0.070705 0.244386 0.289 0.775
## financial_ins_patuniq_mean 0.194029 0.234774 0.826 0.417
## physical_health_both_mean -0.001765 0.192783 -0.009 0.993
## psycsocemo_health_patuniq_mean 0.248775 0.372309 0.668 0.511
## negative_exp_gen_patuniq_mean 0.330291 0.322766 1.023 0.317
## res_aware_patuniq_mean -0.444111 0.274838 -1.616 0.120
## res_use_patuniq_mean -0.006710 0.381949 -0.018 0.986
## pat_childcare_patuniq_mean 0.306634 0.434822 0.705 0.488
## child_issues_patuniq_mean 0.321132 0.357392 0.899 0.379
##
## Residual standard error: 0.9182 on 22 degrees of freedom
## (699 observations deleted due to missingness)
## Multiple R-squared: 0.6248, Adjusted R-squared: 0.352
## F-statistic: 2.29 on 16 and 22 DF, p-value: 0.03611reg_academic_diffty_patuniq_weighted<-lm(academic_diffty_patuniq_mean~
age + binary_gender + race3 + graduate +
socialsupport_patuniq_mean +
financial_ins_patuniq_mean +
physical_health_both_mean +
psycsocemo_health_patuniq_mean +
negative_exp_gen_patuniq_mean +
res_aware_patuniq_mean +
res_use_patuniq_mean +
pat_childcare_patuniq_mean +
child_issues_patuniq_mean,
data=data, weights = data$finalweight, var.equal=TRUE)
summary(reg_academic_diffty_patuniq_weighted)##
## Call:
## lm(formula = academic_diffty_patuniq_mean ~ age + binary_gender +
## race3 + graduate + socialsupport_patuniq_mean + financial_ins_patuniq_mean +
## physical_health_both_mean + psycsocemo_health_patuniq_mean +
## negative_exp_gen_patuniq_mean + res_aware_patuniq_mean +
## res_use_patuniq_mean + pat_childcare_patuniq_mean + child_issues_patuniq_mean,
## data = data, weights = data$finalweight, var.equal = TRUE)
##
## Weighted Residuals:
## Min 1Q Median 3Q Max
## -5.4054 -1.6838 -0.1414 1.7643 5.2020
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.19219 1.86644 0.639 0.5296
## age -0.01518 0.01995 -0.761 0.4546
## binary_gender2 -0.32059 0.37455 -0.856 0.4013
## race31 0.28166 1.59853 0.176 0.8617
## race32 -0.99374 0.54676 -1.818 0.0828 .
## race33 -0.30287 0.81129 -0.373 0.7125
## race34 -0.87737 0.43493 -2.017 0.0560 .
## graduate1 0.16122 0.35487 0.454 0.6541
## socialsupport_patuniq_mean -0.03509 0.23305 -0.151 0.8817
## financial_ins_patuniq_mean 0.10661 0.22847 0.467 0.6454
## physical_health_both_mean -0.03050 0.19389 -0.157 0.8764
## psycsocemo_health_patuniq_mean 0.11212 0.35071 0.320 0.7522
## negative_exp_gen_patuniq_mean 0.33210 0.29258 1.135 0.2686
## res_aware_patuniq_mean -0.45195 0.25959 -1.741 0.0957 .
## res_use_patuniq_mean -0.06575 0.42332 -0.155 0.8780
## pat_childcare_patuniq_mean 0.48154 0.44257 1.088 0.2884
## child_issues_patuniq_mean 0.38377 0.33523 1.145 0.2646
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.282 on 22 degrees of freedom
## (699 observations deleted due to missingness)
## Multiple R-squared: 0.6911, Adjusted R-squared: 0.4665
## F-statistic: 3.076 on 16 and 22 DF, p-value: 0.007751
Social Support