Dissertation Analyses for ABOVE Poverty Status Only
load(file="/Users/meganwilliams/Desktop/Dissertation/StroopAbove.rdata")
load(file="/Users/meganwilliams/Desktop/Dissertation/StroopBelow.rdata")
library(effects)
library(interactions)
library(rcompanion)
library(car)
Stroop Color-Word Test - Psychological Aggression
Model 1
SCWTlog1 <- glm(PsychAggress ~ StroopMixed + WRATtotal, data=StroopAbove,family = "binomial")
summary(SCWTlog1)
##
## Call:
## glm(formula = PsychAggress ~ StroopMixed + WRATtotal, family = "binomial",
## data = StroopAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2999 0.4247 0.5257 0.6149 0.9417
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.123297 0.905204 0.136 0.8917
## StroopMixed 0.039442 0.015554 2.536 0.0112 *
## WRATtotal 0.007447 0.022207 0.335 0.7374
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 325.37 on 381 degrees of freedom
## Residual deviance: 316.23 on 379 degrees of freedom
## AIC: 322.23
##
## Number of Fisher Scoring iterations: 4
confint(SCWTlog1)
## 2.5 % 97.5 %
## (Intercept) -1.615506226 1.95093998
## StroopMixed 0.009242483 0.07041280
## WRATtotal -0.037144175 0.05026136
exp(cbind(OR = coef(SCWTlog1), confint(SCWTlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 1.131221 0.1987900 7.035297
## StroopMixed 1.040230 1.0092853 1.072951
## WRATtotal 1.007475 0.9635372 1.051546
#Plots
plot(predictorEffect("StroopMixed",SCWTlog1))
Model 3
SCWTlog3 <- glm(PsychAggress ~ (StroopMixed + Sex)^2 + Age + WRATtotal, data = StroopAbove,family = "binomial")
summary(SCWTlog3)
##
## Call:
## glm(formula = PsychAggress ~ (StroopMixed + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = StroopAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4677 0.3588 0.5180 0.6248 1.0003
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.52918 1.43262 1.067 0.2858
## StroopMixed 0.04283 0.02311 1.854 0.0638 .
## SexMen 0.34069 0.92444 0.369 0.7125
## Age -0.03129 0.01783 -1.755 0.0793 .
## WRATtotal 0.01339 0.02224 0.602 0.5472
## StroopMixed:SexMen -0.02491 0.02895 -0.860 0.3895
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 325.37 on 381 degrees of freedom
## Residual deviance: 309.82 on 376 degrees of freedom
## AIC: 321.82
##
## Number of Fisher Scoring iterations: 5
confint(SCWTlog3)
## 2.5 % 97.5 %
## (Intercept) -1.254884897 4.379800019
## StroopMixed -0.001613508 0.089514591
## SexMen -1.477280262 2.161450394
## Age -0.066867046 0.003272209
## WRATtotal -0.031153435 0.056399898
## StroopMixed:SexMen -0.082348008 0.031587244
exp(cbind(OR = coef(SCWTlog3), confint(SCWTlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 4.6143720 0.2851087 79.822069
## StroopMixed 1.0437589 0.9983878 1.093643
## SexMen 1.4059172 0.2282576 8.683723
## Age 0.9691926 0.9353195 1.003278
## WRATtotal 1.0134756 0.9693268 1.058021
## StroopMixed:SexMen 0.9753946 0.9209514 1.032091
##Plots
plot(predictorEffect("StroopMixed",SCWTlog3))
Stroop Color-Word Test - Physical Assault
Model 1
SCWTlog1 <- glm(PhysAssault ~ StroopMixed + WRATtotal, data=StroopAbove,family = "binomial")
summary(SCWTlog1)
##
## Call:
## glm(formula = PhysAssault ~ StroopMixed + WRATtotal, family = "binomial",
## data = StroopAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.5473 -0.4705 -0.4350 -0.3818 2.3818
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.064595 1.321864 -3.075 0.00211 **
## StroopMixed 0.004415 0.018775 0.235 0.81408
## WRATtotal 0.035299 0.031527 1.120 0.26286
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 234.00 on 381 degrees of freedom
## Residual deviance: 231.93 on 379 degrees of freedom
## AIC: 237.93
##
## Number of Fisher Scoring iterations: 5
confint(SCWTlog1)
## 2.5 % 97.5 %
## (Intercept) -6.85365408 -1.64238069
## StroopMixed -0.03235074 0.04145773
## WRATtotal -0.02376572 0.10037451
exp(cbind(OR = coef(SCWTlog1), confint(SCWTlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 0.01716993 0.001055591 0.1935188
## StroopMixed 1.00442501 0.968166952 1.0423291
## WRATtotal 1.03592969 0.976514463 1.1055849
##Plots
plot(predictorEffect("StroopMixed",SCWTlog1))
Model 3
SCWTlog3 <- glm(PhysAssault ~ (StroopMixed + Sex)^2+ Age + WRATtotal, data = StroopAbove,family = "binomial")
summary(SCWTlog3)
##
## Call:
## glm(formula = PhysAssault ~ (StroopMixed + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = StroopAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.8186 -0.4701 -0.3846 -0.2975 2.5623
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.01746 1.81726 -1.660 0.0968 .
## StroopMixed 0.01424 0.02410 0.591 0.5545
## SexMen 1.80928 1.24720 1.451 0.1469
## Age -0.03585 0.02208 -1.624 0.1044
## WRATtotal 0.04609 0.03279 1.405 0.1599
## StroopMixed:SexMen -0.07205 0.03626 -1.987 0.0469 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 234.00 on 381 degrees of freedom
## Residual deviance: 221.74 on 376 degrees of freedom
## AIC: 233.74
##
## Number of Fisher Scoring iterations: 5
confint(SCWTlog3)
## 2.5 % 97.5 %
## (Intercept) -6.69567376 0.459075800
## StroopMixed -0.03294528 0.061947939
## SexMen -0.67423061 4.248893034
## Age -0.08002205 0.006948246
## WRATtotal -0.01503945 0.114109032
## StroopMixed:SexMen -0.14436252 -0.001641460
exp(cbind(OR = coef(SCWTlog3), confint(SCWTlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 0.04892516 0.001236249 1.5826107
## StroopMixed 1.01434342 0.967591505 1.0639070
## SexMen 6.10607871 0.509548311 70.0278510
## Age 0.96478615 0.923095995 1.0069724
## WRATtotal 1.04716858 0.985073080 1.1208743
## StroopMixed:SexMen 0.93048869 0.865573902 0.9983599
##Plots
plot(predictorEffect("StroopMixed",SCWTlog3))
Dissertation Analyses for Below Poverty Status Only
Stroop Color-Word Test - Psychological Aggression
Model 1
SCWTlog1 <- glm(PsychAggress ~ StroopMixed + WRATtotal, data=StroopBelow,family = "binomial")
summary(SCWTlog1)
##
## Call:
## glm(formula = PsychAggress ~ StroopMixed + WRATtotal, family = "binomial",
## data = StroopBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4181 0.3987 0.4787 0.5550 0.8000
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.35676 1.31898 -0.270 0.787
## StroopMixed 0.03090 0.02609 1.184 0.236
## WRATtotal 0.03350 0.03229 1.037 0.300
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 126.06 on 165 degrees of freedom
## Residual deviance: 122.54 on 163 degrees of freedom
## AIC: 128.54
##
## Number of Fisher Scoring iterations: 5
confint(SCWTlog1)
## 2.5 % 97.5 %
## (Intercept) -2.90677054 2.32291278
## StroopMixed -0.02041742 0.08262287
## WRATtotal -0.03125495 0.09658674
exp(cbind(OR = coef(SCWTlog1), confint(SCWTlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 0.6999385 0.05465194 10.205357
## StroopMixed 1.0313792 0.97978961 1.086132
## WRATtotal 1.0340693 0.96922844 1.101405
#Plots
plot(predictorEffect("StroopMixed",SCWTlog1))
Model 3
SCWTlog3 <- glm(PsychAggress ~ (StroopMixed + Sex)^2 + Age + WRATtotal, data = StroopBelow,family = "binomial")
summary(SCWTlog3)
##
## Call:
## glm(formula = PsychAggress ~ (StroopMixed + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = StroopBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.5313 0.3839 0.4837 0.5675 0.8612
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.608300 2.293227 -0.701 0.483
## StroopMixed 0.043540 0.041434 1.051 0.293
## SexMen 0.142206 1.528035 0.093 0.926
## Age 0.021624 0.030238 0.715 0.475
## WRATtotal 0.032175 0.032252 0.998 0.318
## StroopMixed:SexMen -0.006833 0.051495 -0.133 0.894
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 126.06 on 165 degrees of freedom
## Residual deviance: 121.99 on 160 degrees of freedom
## AIC: 133.99
##
## Number of Fisher Scoring iterations: 5
confint(SCWTlog3)
## 2.5 % 97.5 %
## (Intercept) -6.25314541 2.80975444
## StroopMixed -0.03560823 0.12845828
## SexMen -2.87661238 3.17552270
## Age -0.03664372 0.08291913
## WRATtotal -0.03230900 0.09544438
## StroopMixed:SexMen -0.10958616 0.09378193
exp(cbind(OR = coef(SCWTlog3), confint(SCWTlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 0.2002277 0.001924392 16.605840
## StroopMixed 1.0445017 0.965018289 1.137074
## SexMen 1.1528145 0.056325248 23.939330
## Age 1.0218592 0.964019539 1.086454
## WRATtotal 1.0326984 0.968207364 1.100148
## StroopMixed:SexMen 0.9931901 0.896204940 1.098320
##Plots
plot(predictorEffect("StroopMixed",SCWTlog3))
Stroop Color-Word Test - Physical Assault
Model 1
SCWTlog1 <- glm(PhysAssault ~ StroopMixed + WRATtotal, data=StroopBelow,family = "binomial")
summary(SCWTlog1)
##
## Call:
## glm(formula = PhysAssault ~ StroopMixed + WRATtotal, family = "binomial",
## data = StroopBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7618 -0.6328 -0.5951 -0.5374 2.0218
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.59167 1.31550 -1.970 0.0488 *
## StroopMixed 0.01591 0.02351 0.677 0.4986
## WRATtotal 0.01177 0.03104 0.379 0.7044
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 150.65 on 165 degrees of freedom
## Residual deviance: 149.79 on 163 degrees of freedom
## AIC: 155.79
##
## Number of Fisher Scoring iterations: 4
confint(SCWTlog1)
## 2.5 % 97.5 %
## (Intercept) -5.32888834 -0.13336153
## StroopMixed -0.02961156 0.06308590
## WRATtotal -0.04742889 0.07508423
exp(cbind(OR = coef(SCWTlog1), confint(SCWTlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 0.07489491 0.004849458 0.8751486
## StroopMixed 1.01603441 0.970822564 1.0651183
## WRATtotal 1.01184389 0.953678290 1.0779749
##Plots
plot(predictorEffect("StroopMixed",SCWTlog1))
Model 3
SCWTlog3 <- glm(PhysAssault ~ (StroopMixed + Sex)^2+ Age + WRATtotal, data = StroopBelow,family = "binomial")
summary(SCWTlog3)
##
## Call:
## glm(formula = PhysAssault ~ (StroopMixed + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = StroopBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7582 -0.6391 -0.5797 -0.5020 2.0639
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.408863 1.981845 -0.711 0.477
## StroopMixed 0.005099 0.033690 0.151 0.880
## SexMen -0.200251 1.501423 -0.133 0.894
## Age -0.021126 0.025488 -0.829 0.407
## WRATtotal 0.013664 0.031048 0.440 0.660
## StroopMixed:SexMen 0.006575 0.045514 0.144 0.885
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 150.65 on 165 degrees of freedom
## Residual deviance: 149.05 on 160 degrees of freedom
## AIC: 161.05
##
## Number of Fisher Scoring iterations: 4
confint(SCWTlog3)
## 2.5 % 97.5 %
## (Intercept) -5.33305942 2.49562431
## StroopMixed -0.06153089 0.07194844
## SexMen -3.20659714 2.74300462
## Age -0.07256563 0.02805610
## WRATtotal -0.04567362 0.07693745
## StroopMixed:SexMen -0.08247322 0.09717083
exp(cbind(OR = coef(SCWTlog3), confint(SCWTlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 0.2444210 0.004829273 12.129304
## StroopMixed 1.0051120 0.940323901 1.074600
## SexMen 0.8185257 0.040494175 15.533588
## Age 0.9790957 0.930004707 1.028453
## WRATtotal 1.0137582 0.955353721 1.079975
## StroopMixed:SexMen 1.0065968 0.920836101 1.102049
##Plots
plot(predictorEffect("StroopMixed",SCWTlog3))
