Attaching Data
Checking Packages
Centering Variables
Correlation
library ("corrplot")## corrplot 0.84 loadedlibrary("Hmisc")## Loading required package: lattice## Loading required package: survival## Loading required package: Formula##
## Attaching package: 'Hmisc'## The following objects are masked from 'package:dplyr':
##
## src, summarize## The following object is masked from 'package:sjmisc':
##
## %nin%## The following object is masked from 'package:psych':
##
## describe## The following objects are masked from 'package:base':
##
## format.pval, unitsmydata<-WJ_RED_Data[, c(2,3,4,5,10,12,13,14,15,16,17 )]
head(mydata)mydata.cor= cor(mydata, method= c("spearman"))
mydata.r.corr= rcorr(as.matrix(mydata))
mydata.r.corr## DeltaDSyMAverage DeltaDSyMSum
## DeltaDSyMAverage 1.00 0.66
## DeltaDSyMSum 0.66 1.00
## PhonemeDiscrepancyAverage 0.51 0.17
## PhonemeDiscrepancySum 0.41 0.71
## RealWordProportion 0.06 0.55
## rc3_wj_lwid_ss_age 0.04 -0.41
## rc3_wj_wa_ss_age -0.01 -0.42
## rc3_wj_pc_ss_age 0.01 -0.34
## rc3_wj_oc_ss_grade 0.15 -0.07
## rc3_knowit_complit_raw -0.02 -0.18
## rc3_wmtb_list_ss 0.09 -0.06
## PhonemeDiscrepancyAverage PhonemeDiscrepancySum
## DeltaDSyMAverage 0.51 0.41
## DeltaDSyMSum 0.17 0.71
## PhonemeDiscrepancyAverage 1.00 0.45
## PhonemeDiscrepancySum 0.45 1.00
## RealWordProportion -0.04 0.62
## rc3_wj_lwid_ss_age 0.31 -0.29
## rc3_wj_wa_ss_age 0.27 -0.37
## rc3_wj_pc_ss_age 0.17 -0.23
## rc3_wj_oc_ss_grade 0.16 -0.12
## rc3_knowit_complit_raw 0.13 -0.08
## rc3_wmtb_list_ss 0.13 0.00
## RealWordProportion rc3_wj_lwid_ss_age
## DeltaDSyMAverage 0.06 0.04
## DeltaDSyMSum 0.55 -0.41
## PhonemeDiscrepancyAverage -0.04 0.31
## PhonemeDiscrepancySum 0.62 -0.29
## RealWordProportion 1.00 -0.59
## rc3_wj_lwid_ss_age -0.59 1.00
## rc3_wj_wa_ss_age -0.56 0.84
## rc3_wj_pc_ss_age -0.35 0.71
## rc3_wj_oc_ss_grade -0.20 0.40
## rc3_knowit_complit_raw -0.13 0.31
## rc3_wmtb_list_ss -0.14 0.33
## rc3_wj_wa_ss_age rc3_wj_pc_ss_age rc3_wj_oc_ss_grade
## DeltaDSyMAverage -0.01 0.01 0.15
## DeltaDSyMSum -0.42 -0.34 -0.07
## PhonemeDiscrepancyAverage 0.27 0.17 0.16
## PhonemeDiscrepancySum -0.37 -0.23 -0.12
## RealWordProportion -0.56 -0.35 -0.20
## rc3_wj_lwid_ss_age 0.84 0.71 0.40
## rc3_wj_wa_ss_age 1.00 0.59 0.40
## rc3_wj_pc_ss_age 0.59 1.00 0.64
## rc3_wj_oc_ss_grade 0.40 0.64 1.00
## rc3_knowit_complit_raw 0.20 0.33 0.50
## rc3_wmtb_list_ss 0.30 0.31 0.36
## rc3_knowit_complit_raw rc3_wmtb_list_ss
## DeltaDSyMAverage -0.02 0.09
## DeltaDSyMSum -0.18 -0.06
## PhonemeDiscrepancyAverage 0.13 0.13
## PhonemeDiscrepancySum -0.08 0.00
## RealWordProportion -0.13 -0.14
## rc3_wj_lwid_ss_age 0.31 0.33
## rc3_wj_wa_ss_age 0.20 0.30
## rc3_wj_pc_ss_age 0.33 0.31
## rc3_wj_oc_ss_grade 0.50 0.36
## rc3_knowit_complit_raw 1.00 0.22
## rc3_wmtb_list_ss 0.22 1.00
##
## n
## DeltaDSyMAverage DeltaDSyMSum
## DeltaDSyMAverage 121 121
## DeltaDSyMSum 121 121
## PhonemeDiscrepancyAverage 121 121
## PhonemeDiscrepancySum 121 121
## RealWordProportion 121 121
## rc3_wj_lwid_ss_age 121 121
## rc3_wj_wa_ss_age 121 121
## rc3_wj_pc_ss_age 121 121
## rc3_wj_oc_ss_grade 113 113
## rc3_knowit_complit_raw 117 117
## rc3_wmtb_list_ss 116 116
## PhonemeDiscrepancyAverage PhonemeDiscrepancySum
## DeltaDSyMAverage 121 121
## DeltaDSyMSum 121 121
## PhonemeDiscrepancyAverage 141 141
## PhonemeDiscrepancySum 141 141
## RealWordProportion 141 141
## rc3_wj_lwid_ss_age 141 141
## rc3_wj_wa_ss_age 141 141
## rc3_wj_pc_ss_age 141 141
## rc3_wj_oc_ss_grade 131 131
## rc3_knowit_complit_raw 135 135
## rc3_wmtb_list_ss 133 133
## RealWordProportion rc3_wj_lwid_ss_age
## DeltaDSyMAverage 121 121
## DeltaDSyMSum 121 121
## PhonemeDiscrepancyAverage 141 141
## PhonemeDiscrepancySum 141 141
## RealWordProportion 165 165
## rc3_wj_lwid_ss_age 165 165
## rc3_wj_wa_ss_age 165 165
## rc3_wj_pc_ss_age 165 165
## rc3_wj_oc_ss_grade 155 155
## rc3_knowit_complit_raw 159 159
## rc3_wmtb_list_ss 157 157
## rc3_wj_wa_ss_age rc3_wj_pc_ss_age rc3_wj_oc_ss_grade
## DeltaDSyMAverage 121 121 113
## DeltaDSyMSum 121 121 113
## PhonemeDiscrepancyAverage 141 141 131
## PhonemeDiscrepancySum 141 141 131
## RealWordProportion 165 165 155
## rc3_wj_lwid_ss_age 165 165 155
## rc3_wj_wa_ss_age 166 165 156
## rc3_wj_pc_ss_age 165 166 156
## rc3_wj_oc_ss_grade 156 156 157
## rc3_knowit_complit_raw 160 160 157
## rc3_wmtb_list_ss 158 158 154
## rc3_knowit_complit_raw rc3_wmtb_list_ss
## DeltaDSyMAverage 117 116
## DeltaDSyMSum 117 116
## PhonemeDiscrepancyAverage 135 133
## PhonemeDiscrepancySum 135 133
## RealWordProportion 159 157
## rc3_wj_lwid_ss_age 159 157
## rc3_wj_wa_ss_age 160 158
## rc3_wj_pc_ss_age 160 158
## rc3_wj_oc_ss_grade 157 154
## rc3_knowit_complit_raw 161 158
## rc3_wmtb_list_ss 158 159
##
## P
## DeltaDSyMAverage DeltaDSyMSum
## DeltaDSyMAverage 0.0000
## DeltaDSyMSum 0.0000
## PhonemeDiscrepancyAverage 0.0000 0.0647
## PhonemeDiscrepancySum 0.0000 0.0000
## RealWordProportion 0.4957 0.0000
## rc3_wj_lwid_ss_age 0.6874 0.0000
## rc3_wj_wa_ss_age 0.9272 0.0000
## rc3_wj_pc_ss_age 0.8965 0.0001
## rc3_wj_oc_ss_grade 0.1024 0.4909
## rc3_knowit_complit_raw 0.8366 0.0541
## rc3_wmtb_list_ss 0.3301 0.5492
## PhonemeDiscrepancyAverage PhonemeDiscrepancySum
## DeltaDSyMAverage 0.0000 0.0000
## DeltaDSyMSum 0.0647 0.0000
## PhonemeDiscrepancyAverage 0.0000
## PhonemeDiscrepancySum 0.0000
## RealWordProportion 0.6147 0.0000
## rc3_wj_lwid_ss_age 0.0002 0.0005
## rc3_wj_wa_ss_age 0.0011 0.0000
## rc3_wj_pc_ss_age 0.0488 0.0061
## rc3_wj_oc_ss_grade 0.0641 0.1661
## rc3_knowit_complit_raw 0.1462 0.3863
## rc3_wmtb_list_ss 0.1320 0.9595
## RealWordProportion rc3_wj_lwid_ss_age
## DeltaDSyMAverage 0.4957 0.6874
## DeltaDSyMSum 0.0000 0.0000
## PhonemeDiscrepancyAverage 0.6147 0.0002
## PhonemeDiscrepancySum 0.0000 0.0005
## RealWordProportion 0.0000
## rc3_wj_lwid_ss_age 0.0000
## rc3_wj_wa_ss_age 0.0000 0.0000
## rc3_wj_pc_ss_age 0.0000 0.0000
## rc3_wj_oc_ss_grade 0.0111 0.0000
## rc3_knowit_complit_raw 0.1127 0.0000
## rc3_wmtb_list_ss 0.0817 0.0000
## rc3_wj_wa_ss_age rc3_wj_pc_ss_age rc3_wj_oc_ss_grade
## DeltaDSyMAverage 0.9272 0.8965 0.1024
## DeltaDSyMSum 0.0000 0.0001 0.4909
## PhonemeDiscrepancyAverage 0.0011 0.0488 0.0641
## PhonemeDiscrepancySum 0.0000 0.0061 0.1661
## RealWordProportion 0.0000 0.0000 0.0111
## rc3_wj_lwid_ss_age 0.0000 0.0000 0.0000
## rc3_wj_wa_ss_age 0.0000 0.0000
## rc3_wj_pc_ss_age 0.0000 0.0000
## rc3_wj_oc_ss_grade 0.0000 0.0000
## rc3_knowit_complit_raw 0.0104 0.0000 0.0000
## rc3_wmtb_list_ss 0.0002 0.0000 0.0000
## rc3_knowit_complit_raw rc3_wmtb_list_ss
## DeltaDSyMAverage 0.8366 0.3301
## DeltaDSyMSum 0.0541 0.5492
## PhonemeDiscrepancyAverage 0.1462 0.1320
## PhonemeDiscrepancySum 0.3863 0.9595
## RealWordProportion 0.1127 0.0817
## rc3_wj_lwid_ss_age 0.0000 0.0000
## rc3_wj_wa_ss_age 0.0104 0.0002
## rc3_wj_pc_ss_age 0.0000 0.0000
## rc3_wj_oc_ss_grade 0.0000 0.0000
## rc3_knowit_complit_raw 0.0063
## rc3_wmtb_list_ss 0.0063RED Models
M1 = lm(zWJPC~ zDeltaDSyMAverage ,data = WJ_RED_Data)
summary(M1)##
## Call:
## lm(formula = zWJPC ~ zDeltaDSyMAverage, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.67425 -0.67576 -0.04931 0.47238 2.43671
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.13787 0.08915 -1.546 0.125
## zDeltaDSyMAverage 0.01167 0.08952 0.130 0.896
##
## Residual standard error: 0.9807 on 119 degrees of freedom
## (79 observations deleted due to missingness)
## Multiple R-squared: 0.0001428, Adjusted R-squared: -0.008259
## F-statistic: 0.017 on 1 and 119 DF, p-value: 0.8965M2 = lm(zWJPC~ zDeltaDSyMSum ,data = WJ_RED_Data)
summary(M2)##
## Call:
## lm(formula = zWJPC ~ zDeltaDSyMSum, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.23503 -0.64150 -0.07304 0.66349 2.49711
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.13787 0.08389 -1.644 0.102913
## zDeltaDSyMSum -0.33087 0.08424 -3.928 0.000144 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9228 on 119 degrees of freedom
## (79 observations deleted due to missingness)
## Multiple R-squared: 0.1148, Adjusted R-squared: 0.1073
## F-statistic: 15.43 on 1 and 119 DF, p-value: 0.0001442M3 = lm(zWJPC~ zPhonemeDiscrepancyAverage ,data = WJ_RED_Data)
summary(M3)##
## Call:
## lm(formula = zWJPC ~ zPhonemeDiscrepancyAverage, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.6344 -0.5833 0.0338 0.4982 3.2835
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.10251 0.08284 -1.237 0.2180
## zPhonemeDiscrepancyAverage 0.16523 0.08313 1.988 0.0488 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9836 on 139 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.02763, Adjusted R-squared: 0.02064
## F-statistic: 3.95 on 1 and 139 DF, p-value: 0.04883M4 = lm(zWJPC~ zPhonemeDiscrepancySum ,data = WJ_RED_Data)
summary(M4)##
## Call:
## lm(formula = zWJPC ~ zPhonemeDiscrepancySum, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.29551 -0.61604 -0.05483 0.51387 2.79118
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.10251 0.08176 -1.254 0.21202
## zPhonemeDiscrepancySum -0.22837 0.08205 -2.783 0.00613 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9708 on 139 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.05279, Adjusted R-squared: 0.04598
## F-statistic: 7.747 on 1 and 139 DF, p-value: 0.00613Comprehension Models with oral language
OC1 = lm(zWJPC~ zLWID +zWJOC ,data = WJ_RED_Data)
summary(OC1)##
## Call:
## lm(formula = zWJPC ~ zLWID + zWJOC, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.48790 -0.40669 -0.05401 0.37412 1.77930
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.04512 0.04835 0.933 0.352
## zLWID 0.52781 0.05399 9.776 < 2e-16 ***
## zWJOC 0.42008 0.05302 7.923 4.59e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6015 on 152 degrees of freedom
## (45 observations deleted due to missingness)
## Multiple R-squared: 0.6324, Adjusted R-squared: 0.6276
## F-statistic: 130.8 on 2 and 152 DF, p-value: < 2.2e-16OC2 = lm(zWJPC~ zLWID + zWJOC + zDeltaDSyMAverage ,data = WJ_RED_Data)
summary(OC2)##
## Call:
## lm(formula = zWJPC ~ zLWID + zWJOC + zDeltaDSyMAverage, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.25350 -0.38363 -0.01249 0.35731 1.74208
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.06533 0.05442 1.201 0.233
## zLWID 0.57086 0.06127 9.318 1.54e-15 ***
## zWJOC 0.40699 0.05671 7.177 9.13e-11 ***
## zDeltaDSyMAverage -0.04839 0.05394 -0.897 0.372
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5681 on 109 degrees of freedom
## (87 observations deleted due to missingness)
## Multiple R-squared: 0.6578, Adjusted R-squared: 0.6484
## F-statistic: 69.86 on 3 and 109 DF, p-value: < 2.2e-16OC3 = lm(zWJPC~ zLWID + zWJOC + zDeltaDSyMSum ,data = WJ_RED_Data)
summary(OC3)##
## Call:
## lm(formula = zWJPC ~ zLWID + zWJOC + zDeltaDSyMSum, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2430 -0.3831 -0.0112 0.3698 1.7385
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.05903 0.05464 1.080 0.282
## zLWID 0.54410 0.06556 8.299 3.10e-13 ***
## zWJOC 0.40404 0.05615 7.195 8.35e-11 ***
## zDeltaDSyMSum -0.06439 0.05796 -1.111 0.269
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.567 on 109 degrees of freedom
## (87 observations deleted due to missingness)
## Multiple R-squared: 0.6592, Adjusted R-squared: 0.6498
## F-statistic: 70.27 on 3 and 109 DF, p-value: < 2.2e-16OC4 = lm(zWJPC~ zLWID + zWJOC + zPhonemeDiscrepancyAverage ,data = WJ_RED_Data)
summary(OC4)##
## Call:
## lm(formula = zWJPC ~ zLWID + zWJOC + zPhonemeDiscrepancyAverage,
## data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.27276 -0.38292 -0.07588 0.35579 1.72752
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.08126 0.05203 1.562 0.121
## zLWID 0.61858 0.06338 9.760 < 2e-16 ***
## zWJOC 0.41127 0.05585 7.363 1.99e-11 ***
## zPhonemeDiscrepancyAverage -0.08138 0.05565 -1.462 0.146
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5866 on 127 degrees of freedom
## (69 observations deleted due to missingness)
## Multiple R-squared: 0.6525, Adjusted R-squared: 0.6443
## F-statistic: 79.48 on 3 and 127 DF, p-value: < 2.2e-16OC5 = lm(zWJPC~ zLWID + zWJOC + zPhonemeDiscrepancySum ,data = WJ_RED_Data)
summary(OC5)##
## Call:
## lm(formula = zWJPC ~ zLWID + zWJOC + zPhonemeDiscrepancySum,
## data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.26644 -0.37519 -0.04403 0.36726 1.78194
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0760885 0.0524417 1.451 0.149
## zLWID 0.5898858 0.0623072 9.467 < 2e-16 ***
## zWJOC 0.4081804 0.0563093 7.249 3.63e-11 ***
## zPhonemeDiscrepancySum 0.0001884 0.0538340 0.003 0.997
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5915 on 127 degrees of freedom
## (69 observations deleted due to missingness)
## Multiple R-squared: 0.6466, Adjusted R-squared: 0.6383
## F-statistic: 77.47 on 3 and 127 DF, p-value: < 2.2e-16Comprehension models without oral language
C1 = lm(zWJPC~ zLWID ,data = WJ_RED_Data)
summary(C1)##
## Call:
## lm(formula = zWJPC ~ zLWID, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.44542 -0.45247 -0.04079 0.39483 2.29354
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.00611 0.05491 0.111 0.912
## zLWID 0.71091 0.05508 12.907 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7053 on 163 degrees of freedom
## (35 observations deleted due to missingness)
## Multiple R-squared: 0.5055, Adjusted R-squared: 0.5024
## F-statistic: 166.6 on 1 and 163 DF, p-value: < 2.2e-16C2 = lm(zWJPC~ zLWID + zDeltaDSyMAverage ,data = WJ_RED_Data)
summary(C2)##
## Call:
## lm(formula = zWJPC ~ zLWID + zDeltaDSyMAverage, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.29138 -0.51586 -0.01182 0.38751 2.28588
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.007033 0.063116 0.111 0.911
## zLWID 0.729921 0.064139 11.380 <2e-16 ***
## zDeltaDSyMAverage -0.014451 0.062117 -0.233 0.816
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.68 on 118 degrees of freedom
## (79 observations deleted due to missingness)
## Multiple R-squared: 0.5233, Adjusted R-squared: 0.5152
## F-statistic: 64.77 on 2 and 118 DF, p-value: < 2.2e-16C3 = lm(zWJPC~ zLWID + zDeltaDSyMSum ,data = WJ_RED_Data)
summary(C3)##
## Call:
## lm(formula = zWJPC ~ zLWID + zDeltaDSyMSum, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.31159 -0.47053 -0.00169 0.39291 2.25827
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.002709 0.063239 0.043 0.966
## zLWID 0.708141 0.070099 10.102 <2e-16 ***
## zDeltaDSyMSum -0.050246 0.067889 -0.740 0.461
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6786 on 118 degrees of freedom
## (79 observations deleted due to missingness)
## Multiple R-squared: 0.5253, Adjusted R-squared: 0.5173
## F-statistic: 65.29 on 2 and 118 DF, p-value: < 2.2e-16C4 = lm(zWJPC~ zLWID + zPhonemeDiscrepancyAverage ,data = WJ_RED_Data)
summary(C4)##
## Call:
## lm(formula = zWJPC ~ zLWID + zPhonemeDiscrepancyAverage, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.58606 -0.48807 -0.04337 0.40302 2.24953
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.02862 0.05913 0.484 0.629
## zLWID 0.78036 0.06493 12.019 <2e-16 ***
## zPhonemeDiscrepancyAverage -0.06653 0.06142 -1.083 0.281
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.69 on 138 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.5249, Adjusted R-squared: 0.518
## F-statistic: 76.24 on 2 and 138 DF, p-value: < 2.2e-16C5 = lm(zWJPC~ zLWID + zPhonemeDiscrepancySum ,data = WJ_RED_Data)
summary(C5)##
## Call:
## lm(formula = zWJPC ~ zLWID + zPhonemeDiscrepancySum, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.50175 -0.46769 -0.02932 0.36997 2.27734
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.02381 0.05934 0.401 0.689
## zLWID 0.75174 0.06468 11.622 <2e-16 ***
## zPhonemeDiscrepancySum -0.02125 0.06119 -0.347 0.729
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6927 on 138 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.5213, Adjusted R-squared: 0.5144
## F-statistic: 75.14 on 2 and 138 DF, p-value: < 2.2e-16Word Attack Models
W1 = lm(zWJWA~ zLWID ,data = WJ_RED_Data)
summary(W1)##
## Call:
## lm(formula = zWJWA ~ zLWID, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.57084 -0.32062 0.02733 0.35553 1.58526
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.01024 0.04199 -0.244 0.808
## zLWID 0.83633 0.04212 19.857 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5394 on 163 degrees of freedom
## (35 observations deleted due to missingness)
## Multiple R-squared: 0.7075, Adjusted R-squared: 0.7057
## F-statistic: 394.3 on 1 and 163 DF, p-value: < 2.2e-16W2 = lm(zWJWA~ zLWID + zDeltaDSyMAverage ,data = WJ_RED_Data)
summary(W2)##
## Call:
## lm(formula = zWJWA ~ zLWID + zDeltaDSyMAverage, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.27941 -0.28752 0.02061 0.31832 1.55458
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.01973 0.04866 -0.405 0.686
## zLWID 0.85512 0.04945 17.292 <2e-16 ***
## zDeltaDSyMAverage -0.03881 0.04789 -0.810 0.419
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5243 on 118 degrees of freedom
## (79 observations deleted due to missingness)
## Multiple R-squared: 0.7171, Adjusted R-squared: 0.7123
## F-statistic: 149.5 on 2 and 118 DF, p-value: < 2.2e-16W3 = lm(zWJWA~ zLWID + zDeltaDSyMSum ,data = WJ_RED_Data)
summary(W3)##
## Call:
## lm(formula = zWJWA ~ zLWID + zDeltaDSyMSum, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.37134 -0.31373 0.02754 0.33175 1.54581
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.02684 0.04850 -0.553 0.581
## zLWID 0.81929 0.05376 15.241 <2e-16 ***
## zDeltaDSyMSum -0.08131 0.05206 -1.562 0.121
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5204 on 118 degrees of freedom
## (79 observations deleted due to missingness)
## Multiple R-squared: 0.7212, Adjusted R-squared: 0.7165
## F-statistic: 152.7 on 2 and 118 DF, p-value: < 2.2e-16W4 = lm(zWJWA~ zLWID + zPhonemeDiscrepancyAverage,data = WJ_RED_Data)
summary(W4)##
## Call:
## lm(formula = zWJWA ~ zLWID + zPhonemeDiscrepancyAverage, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.53753 -0.30500 0.03441 0.31590 1.62416
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.02627 0.04546 -0.578 0.564
## zLWID 0.82811 0.04992 16.587 <2e-16 ***
## zPhonemeDiscrepancyAverage 0.01281 0.04723 0.271 0.787
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5306 on 138 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.6909, Adjusted R-squared: 0.6864
## F-statistic: 154.2 on 2 and 138 DF, p-value: < 2.2e-16W5 = lm(zWJWA~ zLWID + zPhonemeDiscrepancySum,data = WJ_RED_Data)
summary(W5)##
## Call:
## lm(formula = zWJWA ~ zLWID + zPhonemeDiscrepancySum, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.63029 -0.29150 0.02804 0.32467 1.48382
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.03237 0.04415 -0.733 0.46473
## zLWID 0.79186 0.04813 16.454 < 2e-16 ***
## zPhonemeDiscrepancySum -0.13156 0.04553 -2.890 0.00448 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5154 on 138 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.7084, Adjusted R-squared: 0.7041
## F-statistic: 167.6 on 2 and 138 DF, p-value: < 2.2e-16Real Word Proportion
R1 = lm(zWJPC~ zLWID + zRealWordProportion,data = WJ_RED_Data)
summary(R1)##
## Call:
## lm(formula = zWJPC ~ zLWID + zRealWordProportion, data = WJ_RED_Data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.43890 -0.52416 -0.04174 0.42368 2.29770
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.00611 0.05474 0.112 0.911
## zLWID 0.76736 0.06777 11.323 <2e-16 ***
## zRealWordProportion 0.09630 0.06777 1.421 0.157
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7031 on 162 degrees of freedom
## (35 observations deleted due to missingness)
## Multiple R-squared: 0.5116, Adjusted R-squared: 0.5055
## F-statistic: 84.83 on 2 and 162 DF, p-value: < 2.2e-16r squared
r2(C1)## Warning: 'r2' is deprecated.
## Use 'performance::r2()' instead.
## See help("Deprecated")## # R2 for Linear Regression
##
## R2: 0.505
## adj. R2: 0.502r2(W1)## Warning: 'r2' is deprecated.
## Use 'performance::r2()' instead.
## See help("Deprecated")## # R2 for Linear Regression
##
## R2: 0.708
## adj. R2: 0.706r2(W5)## Warning: 'r2' is deprecated.
## Use 'performance::r2()' instead.
## See help("Deprecated")## # R2 for Linear Regression
##
## R2: 0.708
## adj. R2: 0.704Running analyis with equal columns
detach(WJ_RED_Data)
WJ_RED_Data_Equal <- read.csv("~/Dropbox/Vanderbilt/Cutting Lab/Reading Error Measure (RED)/WJ Analysis/WJ_RED_Data_Equal.csv")
View(WJ_RED_Data_Equal)
attach(WJ_RED_Data_Equal)
WJ_RED_Data_Equal$ID<- as.factor(WJ_RED_Data_Equal$ID)
WJ_RED_Data_Equal$zWJPC<-scale(WJ_RED_Data_Equal$rc3_wj_pc_ss_age, scale=TRUE, center=TRUE)
WJ_RED_Data_Equal$zAge<-scale(WJ_RED_Data_Equal$age, scale=TRUE, center=TRUE)
WJ_RED_Data_Equal$zWJWA<-scale(WJ_RED_Data_Equal$rc3_wj_wa_ss_age, scale=TRUE, center=TRUE)
WJ_RED_Data_Equal$zLWID<-scale(WJ_RED_Data_Equal$rc3_wj_lwid_ss_age, scale=TRUE, center=TRUE)
WJ_RED_Data_Equal$zDeltaDSyMAverage<-scale(WJ_RED_Data_Equal$DeltaDSyMAverage, scale=TRUE, center=TRUE)
WJ_RED_Data_Equal$zDeltaDSyMSum<-scale(WJ_RED_Data_Equal$DeltaDSyMSum, scale=TRUE, center=TRUE)
WJ_RED_Data_Equal$zPhonemeDiscrepancyAverage<-scale(WJ_RED_Data_Equal$PhonemeDiscrepancyAverage, scale=TRUE, center=TRUE)
WJ_RED_Data_Equal$zPhonemeDiscrepancySum<-scale(WJ_RED_Data_Equal$PhonemeDiscrepancySum, scale=TRUE, center=TRUE)
WA1 = lm(zWJWA~ zLWID ,data = WJ_RED_Data_Equal)
summary(WA1)##
## Call:
## lm(formula = zWJWA ~ zLWID, data = WJ_RED_Data_Equal)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.63865 -0.31590 0.04714 0.33490 1.69180
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.580e-17 4.700e-02 0.00 1
## zLWID 8.311e-01 4.717e-02 17.62 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5581 on 139 degrees of freedom
## Multiple R-squared: 0.6907, Adjusted R-squared: 0.6885
## F-statistic: 310.4 on 1 and 139 DF, p-value: < 2.2e-16WA5 = lm(zWJWA~ zLWID + zPhonemeDiscrepancySum,data = WJ_RED_Data_Equal)
summary(WA5)##
## Call:
## lm(formula = zWJWA ~ zLWID + zPhonemeDiscrepancySum, data = WJ_RED_Data_Equal)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.72069 -0.30766 0.02959 0.34268 1.56609
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.799e-17 4.581e-02 0.00 1.00000
## zLWID 7.907e-01 4.805e-02 16.45 < 2e-16 ***
## zPhonemeDiscrepancySum -1.389e-01 4.805e-02 -2.89 0.00448 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5439 on 138 degrees of freedom
## Multiple R-squared: 0.7084, Adjusted R-squared: 0.7041
## F-statistic: 167.6 on 2 and 138 DF, p-value: < 2.2e-16anova(WA1,WA5)r2(WA1)## Warning: 'r2' is deprecated.
## Use 'performance::r2()' instead.
## See help("Deprecated")## # R2 for Linear Regression
##
## R2: 0.691
## adj. R2: 0.688r2(WA5)## Warning: 'r2' is deprecated.
## Use 'performance::r2()' instead.
## See help("Deprecated")## # R2 for Linear Regression
##
## R2: 0.708
## adj. R2: 0.704