RED Poster
Sage Pickren
1/31/2020
Installing and Checking Packages
library("lavaan")
library("effects")
library("psych")
library("lme4")
library("lmerTest")
library("sjstats")
library("sjmisc")
library("lattice")Importing and Attaching Data
library("sjmisc")
setwd("~/Dropbox/Vanderbilt/Cutting Lab/Reading Error Measure (RED)/PCRC/Poster Analyses")
library(readxl)
REDmasterRC3Y2 <- read_excel("REDmasterRC3Y2.xls")
View(REDmasterRC3Y2)
attach(REDmasterRC3Y2)Checking Variable Distributions
histogram(rc3_wj_br_ss_age)
boxplot(rc3_wj_br_ss_age)
histogram(rc3_gates_comp_raw)
histogram(RealWordProportion_E)
histogram(RealWordProportion_N)
histogram(CWPM_E)
histogram(CWPM_N)
histogram(DeltaDSyM_E_Average)
boxplot(DeltaDSyM_E_Average)
histogram(DeltaDSyM_E_Sum)
boxplot(DeltaDSyM_E_Sum)
histogram(DeltaDSyM_N_Average)
boxplot(DeltaDSyM_N_Sum)
Interesting how the real word proportion histogram totally flips for narrative vs. expository A lot of outliers for the DeltaDSyM
DeltaDSyM Linear Models Narrative
M1 <- lm(rc3_wj_br_ss_age ~ CWPM_N +DeltaDSyM_N_Average , data = REDmasterRC3Y2)
summary(M1)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_N + DeltaDSyM_N_Average,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.6423 -6.2798 0.4992 5.7125 21.5808
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.15068 2.44148 34.057 <2e-16 ***
## CWPM_N 0.22403 0.01528 14.661 <2e-16 ***
## DeltaDSyM_N_Average -0.76320 1.86846 -0.408 0.684
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.259 on 152 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.586, Adjusted R-squared: 0.5806
## F-statistic: 107.6 on 2 and 152 DF, p-value: < 2.2e-16M2 <- lm(rc3_wj_br_ss_age ~ CWPM_N + Passage_N+ DeltaDSyM_N_Average , data = REDmasterRC3Y2)
summary(M2)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_N + Passage_N + DeltaDSyM_N_Average,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.1496 -6.0785 0.3091 5.1062 22.0900
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 90.59491 5.29870 17.098 <2e-16 ***
## CWPM_N 0.22381 0.01524 14.683 <2e-16 ***
## Passage_NThe Ants and the Grasshopper -7.97279 4.84836 -1.644 0.102
## Passage_NThe Monkey and the Cat -7.22746 4.85118 -1.490 0.138
## DeltaDSyM_N_Average -0.72096 1.86376 -0.387 0.699
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.237 on 150 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.5936, Adjusted R-squared: 0.5828
## F-statistic: 54.78 on 4 and 150 DF, p-value: < 2.2e-16M3 <- lm(rc3_wj_br_ss_age ~ DeltaDSyM_N_Average , data = REDmasterRC3Y2)
summary(M3)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ DeltaDSyM_N_Average, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -38.705 -9.063 0.604 9.330 30.256
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 106.8036 2.8379 37.635 <2e-16 ***
## DeltaDSyM_N_Average 0.8626 2.8885 0.299 0.766
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 12.79 on 153 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.0005825, Adjusted R-squared: -0.00595
## F-statistic: 0.08918 on 1 and 153 DF, p-value: 0.7656M4 <- lm(rc3_wj_br_ss_age ~ DeltaDSyM_N_Sum , data = REDmasterRC3Y2)
summary(M4)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ DeltaDSyM_N_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -18.686 -7.977 -1.065 6.664 40.248
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 113.38347 1.03469 109.582 <2e-16 ***
## DeltaDSyM_N_Sum -0.59577 0.06448 -9.239 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.25 on 153 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.3581, Adjusted R-squared: 0.3539
## F-statistic: 85.36 on 1 and 153 DF, p-value: < 2.2e-16M5 <- lm(rc3_wj_br_ss_age ~ CWPM_N + DeltaDSyM_N_Sum , data = REDmasterRC3Y2)
summary(M5)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_N + DeltaDSyM_N_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.7579 -6.3099 -0.2563 4.8485 30.7805
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.73483 2.32558 38.586 < 2e-16 ***
## CWPM_N 0.18215 0.01687 10.796 < 2e-16 ***
## DeltaDSyM_N_Sum -0.26586 0.05747 -4.626 7.92e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.737 on 152 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.6367, Adjusted R-squared: 0.6319
## F-statistic: 133.2 on 2 and 152 DF, p-value: < 2.2e-16M6 <- lm(rc3_wj_br_ss_age ~ CWPM_N + Passage_N + DeltaDSyM_N_Sum , data = REDmasterRC3Y2)
summary(M6)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_N + Passage_N + DeltaDSyM_N_Sum,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.3731 -6.0224 -0.3162 4.9093 30.9799
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 96.80240 4.98062 19.436 < 2e-16 ***
## CWPM_N 0.18235 0.01684 10.827 < 2e-16 ***
## Passage_NThe Ants and the Grasshopper -7.49079 4.54376 -1.649 0.101
## Passage_NThe Monkey and the Cat -7.01488 4.54520 -1.543 0.125
## DeltaDSyM_N_Sum -0.26315 0.05740 -4.584 9.53e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.718 on 150 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.6432, Adjusted R-squared: 0.6337
## F-statistic: 67.61 on 4 and 150 DF, p-value: < 2.2e-16*Sum is significant, but average is not.
DeltaDSyM Linear Moels Expository
M7 <- lm(rc3_wj_br_ss_age ~ DeltaDSyM_E_Sum , data = REDmasterRC3Y2)
summary(M7)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ DeltaDSyM_E_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.4442 -6.4318 0.3208 6.7476 24.9755
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 113.38043 0.94352 120.17 <2e-16 ***
## DeltaDSyM_E_Sum -0.60842 0.05642 -10.79 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.749 on 155 degrees of freedom
## (28 observations deleted due to missingness)
## Multiple R-squared: 0.4287, Adjusted R-squared: 0.425
## F-statistic: 116.3 on 1 and 155 DF, p-value: < 2.2e-16M8 <- lm(rc3_wj_br_ss_age ~ CWPM_E + DeltaDSyM_E_Sum , data = REDmasterRC3Y2)
summary(M8)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_E + DeltaDSyM_E_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.9719 -5.4054 -0.0239 5.3161 16.8310
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.43844 2.14576 41.682 < 2e-16 ***
## CWPM_E 0.22457 0.01906 11.780 < 2e-16 ***
## DeltaDSyM_E_Sum -0.27023 0.05016 -5.388 2.64e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.105 on 153 degrees of freedom
## (29 observations deleted due to missingness)
## Multiple R-squared: 0.7002, Adjusted R-squared: 0.6963
## F-statistic: 178.7 on 2 and 153 DF, p-value: < 2.2e-16M9 <- lm(rc3_wj_br_ss_age ~ CWPM_E + Passage_e + DeltaDSyM_E_Sum , data = REDmasterRC3Y2)
summary(M9)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_E + Passage_e + DeltaDSyM_E_Sum,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.4971 -5.2351 -0.3895 5.4922 16.1634
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 88.75193 2.26088 39.255 < 2e-16 ***
## CWPM_E 0.22597 0.01918 11.783 < 2e-16 ***
## Passage_eIgloo 0.40268 7.18154 0.056 0.955
## Passage_eIgloos 1.15430 1.15002 1.004 0.317
## DeltaDSyM_E_Sum -0.26952 0.05038 -5.350 3.21e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.129 on 151 degrees of freedom
## (29 observations deleted due to missingness)
## Multiple R-squared: 0.7022, Adjusted R-squared: 0.6943
## F-statistic: 89.01 on 4 and 151 DF, p-value: < 2.2e-16Real Word Proportion
R1 <- lm(rc3_towk_rec_raw ~ RealWordProportion_E , data = REDmasterRC3Y2)
summary(R1)##
## Call:
## lm(formula = rc3_towk_rec_raw ~ RealWordProportion_E, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13.9098 -2.6792 -0.0381 3.5234 13.0597
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 23.160 2.050 11.296 <2e-16 ***
## RealWordProportion_E 2.034 2.460 0.827 0.41
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.938 on 149 degrees of freedom
## (34 observations deleted due to missingness)
## Multiple R-squared: 0.004568, Adjusted R-squared: -0.002113
## F-statistic: 0.6837 on 1 and 149 DF, p-value: 0.4096R2 <- lm(rc3_towk_rec_raw ~ RealWordProportion_N , data = REDmasterRC3Y2)
summary(R2)##
## Call:
## lm(formula = rc3_towk_rec_raw ~ RealWordProportion_N, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13.4693 -2.7385 0.1925 3.3898 13.5377
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 24.8075 0.7039 35.241 <2e-16 ***
## RealWordProportion_N -0.6904 2.5927 -0.266 0.79
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.896 on 147 degrees of freedom
## (36 observations deleted due to missingness)
## Multiple R-squared: 0.0004821, Adjusted R-squared: -0.006317
## F-statistic: 0.0709 on 1 and 147 DF, p-value: 0.7904R3 <- lm(rc3_towk_rec_raw ~ rc3_wj_br_ss_age + RealWordProportion_E , data = REDmasterRC3Y2)
summary(R3)##
## Call:
## lm(formula = rc3_towk_rec_raw ~ rc3_wj_br_ss_age + RealWordProportion_E,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10.9415 -4.0328 0.0828 3.0817 13.7923
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.33851 4.28418 0.312 0.755
## rc3_wj_br_ss_age 0.19875 0.03521 5.645 8.33e-08 ***
## RealWordProportion_E 2.74007 2.24690 1.219 0.225
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.382 on 146 degrees of freedom
## (36 observations deleted due to missingness)
## Multiple R-squared: 0.1832, Adjusted R-squared: 0.172
## F-statistic: 16.38 on 2 and 146 DF, p-value: 3.829e-07R4 <- lm(rc3_towk_rec_raw ~ rc3_wj_br_ss_age + RealWordProportion_N , data = REDmasterRC3Y2)
summary(R4)##
## Call:
## lm(formula = rc3_towk_rec_raw ~ rc3_wj_br_ss_age + RealWordProportion_N,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -10.6750 -3.8143 0.0152 3.2039 14.1337
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.7256 3.8536 1.226 0.222
## rc3_wj_br_ss_age 0.1872 0.0355 5.275 4.77e-07 ***
## RealWordProportion_N -0.2917 2.3845 -0.122 0.903
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.401 on 144 degrees of freedom
## (38 observations deleted due to missingness)
## Multiple R-squared: 0.1621, Adjusted R-squared: 0.1505
## F-statistic: 13.93 on 2 and 144 DF, p-value: 2.95e-06R5 <- lm(rc3_wj_br_ss_age ~ CWPM_N + RealWordProportion_N , data = REDmasterRC3Y2)
summary(R5)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_N + RealWordProportion_N,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.754 -5.915 0.321 5.593 21.643
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 81.99164 1.97033 41.613 <2e-16 ***
## CWPM_N 0.22383 0.01524 14.687 <2e-16 ***
## RealWordProportion_N 2.36415 3.39393 0.697 0.487
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.251 on 152 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.5869, Adjusted R-squared: 0.5814
## F-statistic: 108 on 2 and 152 DF, p-value: < 2.2e-16R6 <- lm(rc3_wj_br_ss_age ~ CWPM_E + RealWordProportion_E , data = REDmasterRC3Y2)
summary(R6)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_E + RealWordProportion_E,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -22.4921 -5.1401 -0.2874 5.7917 17.2132
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 82.17622 3.07179 26.752 <2e-16 ***
## CWPM_E 0.28382 0.01695 16.740 <2e-16 ***
## RealWordProportion_E -0.97279 3.17550 -0.306 0.76
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.726 on 154 degrees of freedom
## (28 observations deleted due to missingness)
## Multiple R-squared: 0.6454, Adjusted R-squared: 0.6408
## F-statistic: 140.1 on 2 and 154 DF, p-value: < 2.2e-16*Real word proportion doesn’t seem to do anything.
E1 <- lm(rc3_wj_br_ss_age ~ CWPM_E + DeltaDSyM_E_Sum + EndingProportion_E , data = REDmasterRC3Y2)
summary(E1)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_E + DeltaDSyM_E_Sum + EndingProportion_E,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -19.6651 -5.2629 -0.6326 5.4986 16.7046
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 87.77048 2.22315 39.480 < 2e-16 ***
## CWPM_E 0.22665 0.01884 12.032 < 2e-16 ***
## DeltaDSyM_E_Sum -0.25528 0.04963 -5.143 8.26e-07 ***
## EndingProportion_E 5.81115 3.21673 1.807 0.0728 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.987 on 151 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.7127, Adjusted R-squared: 0.707
## F-statistic: 124.9 on 3 and 151 DF, p-value: < 2.2e-16E2 <- lm(rc3_wj_br_ss_age ~ CWPM_N + DeltaDSyM_N_Sum + EndingProportion_N , data = REDmasterRC3Y2)
summary(E2)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_N + DeltaDSyM_N_Sum + EndingProportion_N,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.7063 -6.3061 -0.2794 4.8591 30.7961
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.65960 2.50485 35.794 < 2e-16 ***
## CWPM_N 0.18228 0.01700 10.724 < 2e-16 ***
## DeltaDSyM_N_Sum -0.26517 0.05826 -4.552 1.09e-05 ***
## EndingProportion_N 0.26633 3.22622 0.083 0.934
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.762 on 151 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.6367, Adjusted R-squared: 0.6295
## F-statistic: 88.22 on 3 and 151 DF, p-value: < 2.2e-16E3 <- lm(rc3_wj_br_ss_age ~ CWPM_E + EndingProportion_E , data = REDmasterRC3Y2)
summary(E3)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_E + EndingProportion_E,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -20.9739 -4.9583 -0.5819 5.5942 18.3197
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 79.90508 1.74186 45.873 <2e-16 ***
## CWPM_E 0.28234 0.01662 16.986 <2e-16 ***
## EndingProportion_E 7.05235 3.45591 2.041 0.043 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 7.528 on 153 degrees of freedom
## (29 observations deleted due to missingness)
## Multiple R-squared: 0.6641, Adjusted R-squared: 0.6597
## F-statistic: 151.3 on 2 and 153 DF, p-value: < 2.2e-16E4 <- lm(rc3_wj_br_ss_age ~ CWPM_N + EndingProportion_N , data = REDmasterRC3Y2)
summary(E4)##
## Call:
## lm(formula = rc3_wj_br_ss_age ~ CWPM_N + EndingProportion_N,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.754 -5.915 0.321 5.593 21.643
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 81.99164 1.97033 41.613 <2e-16 ***
## CWPM_N 0.22383 0.01524 14.687 <2e-16 ***
## EndingProportion_N 2.36415 3.39393 0.697 0.487
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 8.251 on 152 degrees of freedom
## (30 observations deleted due to missingness)
## Multiple R-squared: 0.5869, Adjusted R-squared: 0.5814
## F-statistic: 108 on 2 and 152 DF, p-value: < 2.2e-16*So for expository only, if you make more errors that are just messing up the ending of words, tehn you are a better overall reader after controlling for words correct per minute.
Comprehension
C1 <- lm(rc3_wj_pc_raw_age ~ CWPM_E + DeltaDSyM_E_Sum , data = REDmasterRC3Y2)
summary(C1)##
## Call:
## lm(formula = rc3_wj_pc_raw_age ~ CWPM_E + DeltaDSyM_E_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.0128 -2.1682 0.0869 2.2394 6.4206
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 23.165621 0.896061 25.853 <2e-16 ***
## CWPM_E 0.080554 0.007981 10.094 <2e-16 ***
## DeltaDSyM_E_Sum -0.035217 0.021048 -1.673 0.0963 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.992 on 154 degrees of freedom
## (28 observations deleted due to missingness)
## Multiple R-squared: 0.543, Adjusted R-squared: 0.537
## F-statistic: 91.48 on 2 and 154 DF, p-value: < 2.2e-16C2 <- lm(rc3_wj_pc_raw_age ~ CWPM_N + DeltaDSyM_N_Sum , data = REDmasterRC3Y2)
summary(C2)##
## Call:
## lm(formula = rc3_wj_pc_raw_age ~ CWPM_N + DeltaDSyM_N_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.6707 -1.8317 0.1626 2.0845 6.8713
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 23.545775 0.900595 26.145 <2e-16 ***
## CWPM_N 0.063632 0.006551 9.713 <2e-16 ***
## DeltaDSyM_N_Sum -0.052280 0.022398 -2.334 0.0209 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.027 on 153 degrees of freedom
## (29 observations deleted due to missingness)
## Multiple R-squared: 0.5281, Adjusted R-squared: 0.522
## F-statistic: 85.62 on 2 and 153 DF, p-value: < 2.2e-16C3 <- lm(rc3_gates_comp_raw ~ CWPM_N + DeltaDSyM_N_Sum , data = REDmasterRC3Y2)
summary(C3)##
## Call:
## lm(formula = rc3_gates_comp_raw ~ CWPM_N + DeltaDSyM_N_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -14.3127 -4.4153 -0.2315 4.6118 15.3100
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15.38239 1.81968 8.453 2.23e-14 ***
## CWPM_N 0.16349 0.01318 12.403 < 2e-16 ***
## DeltaDSyM_N_Sum -0.11448 0.04543 -2.520 0.0128 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.118 on 151 degrees of freedom
## (31 observations deleted due to missingness)
## Multiple R-squared: 0.6358, Adjusted R-squared: 0.631
## F-statistic: 131.8 on 2 and 151 DF, p-value: < 2.2e-16C4 <- lm(rc3_gates_comp_raw ~ CWPM_E + DeltaDSyM_E_Sum , data = REDmasterRC3Y2)
summary(C4)##
## Call:
## lm(formula = rc3_gates_comp_raw ~ CWPM_E + DeltaDSyM_E_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.5462 -3.7698 -0.3809 3.7813 15.3752
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15.70929 1.77722 8.839 2.32e-15 ***
## CWPM_E 0.19744 0.01567 12.603 < 2e-16 ***
## DeltaDSyM_E_Sum -0.13174 0.04448 -2.962 0.00356 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.948 on 151 degrees of freedom
## (31 observations deleted due to missingness)
## Multiple R-squared: 0.6592, Adjusted R-squared: 0.6546
## F-statistic: 146 on 2 and 151 DF, p-value: < 2.2e-16C5 <- lm(rc3_gates_comp_raw ~ CWPM_E + DeltaDSyM_E_Average , data = REDmasterRC3Y2)
summary(C5)##
## Call:
## lm(formula = rc3_gates_comp_raw ~ CWPM_E + DeltaDSyM_E_Average,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.126 -4.720 0.000 3.851 17.101
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10.20572 1.65369 6.171 5.94e-09 ***
## CWPM_E 0.22365 0.01341 16.673 < 2e-16 ***
## DeltaDSyM_E_Average 2.53395 1.21631 2.083 0.0389 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.032 on 151 degrees of freedom
## (31 observations deleted due to missingness)
## Multiple R-squared: 0.6494, Adjusted R-squared: 0.6448
## F-statistic: 139.9 on 2 and 151 DF, p-value: < 2.2e-16C6 <- lm(rc3_gates_comp_raw ~ CWPM_N + DeltaDSyM_N_Average , data = REDmasterRC3Y2)
summary(C6)##
## Call:
## lm(formula = rc3_gates_comp_raw ~ CWPM_N + DeltaDSyM_N_Average,
## data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -15.2677 -4.4732 -0.3118 4.4864 16.2857
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11.44467 1.77626 6.443 1.48e-09 ***
## CWPM_N 0.17979 0.01153 15.589 < 2e-16 ***
## DeltaDSyM_N_Average 1.09546 1.33725 0.819 0.414
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 6.232 on 151 degrees of freedom
## (31 observations deleted due to missingness)
## Multiple R-squared: 0.6222, Adjusted R-squared: 0.6172
## F-statistic: 124.3 on 2 and 151 DF, p-value: < 2.2e-16*If you have further discrepancy between the printed text and your miscues, then your comprehension is worse, after controlling for CWPM. Works for both WJPC and Gates. DeltaDSyM Average is significnat for expository when predicitng gates comp.
Interactions with EF
I1 <- lm(rc3_gates_comp_raw ~ CWPM_E*DeltaDSyM_E_Sum*rc3_spspan_tot_raw , data = REDmasterRC3Y2)
summary(I1)##
## Call:
## lm(formula = rc3_gates_comp_raw ~ CWPM_E * DeltaDSyM_E_Sum *
## rc3_spspan_tot_raw, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.0951 -3.6379 -0.0597 3.7319 14.8223
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 5.0983244 6.2397150 0.817
## CWPM_E 0.2493926 0.0569213 4.381
## DeltaDSyM_E_Sum 0.2718228 0.2736927 0.993
## rc3_spspan_tot_raw 0.9713422 0.4934688 1.968
## CWPM_E:DeltaDSyM_E_Sum -0.0007894 0.0063479 -0.124
## CWPM_E:rc3_spspan_tot_raw -0.0062811 0.0044999 -1.396
## DeltaDSyM_E_Sum:rc3_spspan_tot_raw -0.0598938 0.0262351 -2.283
## CWPM_E:DeltaDSyM_E_Sum:rc3_spspan_tot_raw 0.0005825 0.0005206 1.119
## Pr(>|t|)
## (Intercept) 0.4152
## CWPM_E 2.27e-05 ***
## DeltaDSyM_E_Sum 0.3223
## rc3_spspan_tot_raw 0.0510 .
## CWPM_E:DeltaDSyM_E_Sum 0.9012
## CWPM_E:rc3_spspan_tot_raw 0.1649
## DeltaDSyM_E_Sum:rc3_spspan_tot_raw 0.0239 *
## CWPM_E:DeltaDSyM_E_Sum:rc3_spspan_tot_raw 0.2651
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.709 on 143 degrees of freedom
## (34 observations deleted due to missingness)
## Multiple R-squared: 0.6883, Adjusted R-squared: 0.6731
## F-statistic: 45.12 on 7 and 143 DF, p-value: < 2.2e-16I2 <- lm(rc3_gates_comp_raw ~ CWPM_E+ DeltaDSyM_E_Sum*rc3_spspan_tot_raw , data = REDmasterRC3Y2)
summary(I2)##
## Call:
## lm(formula = rc3_gates_comp_raw ~ CWPM_E + DeltaDSyM_E_Sum *
## rc3_spspan_tot_raw, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.680 -3.661 -0.361 4.430 14.343
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11.98976 2.52527 4.748 4.86e-06 ***
## CWPM_E 0.18999 0.01621 11.719 < 2e-16 ***
## DeltaDSyM_E_Sum 0.02930 0.11755 0.249 0.8035
## rc3_spspan_tot_raw 0.37348 0.15853 2.356 0.0198 *
## DeltaDSyM_E_Sum:rc3_spspan_tot_raw -0.01615 0.01171 -1.378 0.1702
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.903 on 146 degrees of freedom
## (34 observations deleted due to missingness)
## Multiple R-squared: 0.6599, Adjusted R-squared: 0.6505
## F-statistic: 70.81 on 4 and 146 DF, p-value: < 2.2e-16I3 <- lm(rc3_gates_comp_raw ~ CWPM_E + rc3_spspan_tot_raw + DeltaDSyM_E_Sum , data = REDmasterRC3Y2)
summary(I3)##
## Call:
## lm(formula = rc3_gates_comp_raw ~ CWPM_E + rc3_spspan_tot_raw +
## DeltaDSyM_E_Sum, data = REDmasterRC3Y2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -12.3943 -3.7906 0.1237 4.1409 14.7414
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12.80338 2.46282 5.199 6.61e-07 ***
## CWPM_E 0.19506 0.01584 12.318 < 2e-16 ***
## rc3_spspan_tot_raw 0.24406 0.12813 1.905 0.0588 .
## DeltaDSyM_E_Sum -0.11792 0.04925 -2.394 0.0179 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.921 on 147 degrees of freedom
## (34 observations deleted due to missingness)
## Multiple R-squared: 0.6554, Adjusted R-squared: 0.6484
## F-statistic: 93.21 on 3 and 147 DF, p-value: < 2.2e-16Delta dsym sum is stil significnat, even after controlling for EF in predicting comprhension.