Dissertation Analyses for ABOVE Poverty Status Only
load(file="/Users/meganwilliams/Desktop/Dissertation/AllvarsAbove.rdata")
load(file="/Users/meganwilliams/Desktop/Dissertation/AllvarsBelow.rdata")
library(effects)
library(interactions)
library(rcompanion)
library(car)
Trail Making Test Part A - Psychological Aggression
Model 1
TMTAlog1 <- glm(PsychAggress ~ TrailsA + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(TMTAlog1)
##
## Call:
## glm(formula = PsychAggress ~ TrailsA + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.0801 0.5046 0.5323 0.5679 1.0320
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.172084 0.786682 1.490 0.1362
## TrailsA -0.005289 0.003022 -1.750 0.0801 .
## WRATtotal 0.018251 0.017263 1.057 0.2904
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 364.97 on 439 degrees of freedom
## Residual deviance: 360.60 on 437 degrees of freedom
## AIC: 366.6
##
## Number of Fisher Scoring iterations: 4
confint(TMTAlog1)
## 2.5 % 97.5 %
## (Intercept) -0.33213279 2.768378934
## TrailsA -0.01120548 0.001165937
## WRATtotal -0.01638549 0.051607639
exp(cbind(OR = coef(TMTAlog1), confint(TMTAlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 3.2287142 0.7173921 15.932785
## TrailsA 0.9947251 0.9888571 1.001167
## WRATtotal 1.0184190 0.9837480 1.052963
#Plots
plot(predictorEffect("TrailsA",TMTAlog1))
Model 3
TMTAlog3 <- glm(PsychAggress ~ (TrailsA + Sex)^2 + Age + WRATtotal, data = AllvarsAbove,family = "binomial")
summary(TMTAlog3)
##
## Call:
## glm(formula = PsychAggress ~ (TrailsA + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3655 0.4105 0.5040 0.5985 0.9513
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.9930072 1.1102929 2.696 0.00702 **
## TrailsA -0.0040619 0.0045052 -0.902 0.36726
## SexMen -0.5078855 0.3783352 -1.342 0.17946
## Age -0.0334762 0.0156375 -2.141 0.03229 *
## WRATtotal 0.0193238 0.0173756 1.112 0.26609
## TrailsA:SexMen -0.0002016 0.0061890 -0.033 0.97401
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 364.97 on 439 degrees of freedom
## Residual deviance: 352.11 on 434 degrees of freedom
## AIC: 364.11
##
## Number of Fisher Scoring iterations: 4
confint(TMTAlog3)
## 2.5 % 97.5 %
## (Intercept) 0.85903566 5.223517800
## TrailsA -0.01277002 0.006535673
## SexMen -1.26023672 0.232998521
## Age -0.06461079 -0.003114333
## WRATtotal -0.01547552 0.052932372
## TrailsA:SexMen -0.01317673 0.012361259
exp(cbind(OR = coef(TMTAlog3), confint(TMTAlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 19.9455725 2.3608829 185.5858911
## TrailsA 0.9959463 0.9873112 1.0065571
## SexMen 0.6017667 0.2835869 1.2623796
## Age 0.9670779 0.9374323 0.9968905
## WRATtotal 1.0195117 0.9846436 1.0543583
## TrailsA:SexMen 0.9997984 0.9869097 1.0124380
##Plots
plot(predictorEffect("TrailsA",TMTAlog3))
Trail Making Test Part A - Physical Assault
Model 1
TMTAlog1 <- glm(PhysAssault ~ TrailsA + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(TMTAlog1)
##
## Call:
## glm(formula = PhysAssault ~ TrailsA + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.5187 -0.4890 -0.4719 -0.4475 2.3056
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.340965 1.102107 -2.124 0.0337 *
## TrailsA -0.005850 0.008008 -0.731 0.4651
## WRATtotal 0.008710 0.022294 0.391 0.6960
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 294.76 on 439 degrees of freedom
## Residual deviance: 293.60 on 437 degrees of freedom
## AIC: 299.6
##
## Number of Fisher Scoring iterations: 5
confint(TMTAlog1)
## 2.5 % 97.5 %
## (Intercept) -4.54856926 -0.141627889
## TrailsA -0.02802721 0.004892201
## WRATtotal -0.03405135 0.053952056
exp(cbind(OR = coef(TMTAlog1), confint(TMTAlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 0.09623472 0.01058233 0.8679442
## TrailsA 0.99416716 0.97236191 1.0049042
## WRATtotal 1.00874764 0.96652187 1.0554340
##Plots
plot(predictorEffect("TrailsA",TMTAlog1))
Model 3
TMTAlog3 <- glm(PhysAssault ~ (TrailsA + Sex)^2+ Age + WRATtotal, data = AllvarsAbove,family = "binomial")
summary(TMTAlog3)
##
## Call:
## glm(formula = PhysAssault ~ (TrailsA + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6248 -0.5114 -0.4489 -0.3928 2.3962
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.0742213 1.3213434 -0.813 0.4162
## TrailsA -0.0001742 0.0075143 -0.023 0.9815
## SexMen 0.1000549 0.5913044 0.169 0.8656
## Age -0.0296540 0.0180052 -1.647 0.0996 .
## WRATtotal 0.0090076 0.0224890 0.401 0.6888
## TrailsA:SexMen -0.0085098 0.0158933 -0.535 0.5924
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 294.76 on 439 degrees of freedom
## Residual deviance: 290.11 on 434 degrees of freedom
## AIC: 302.11
##
## Number of Fisher Scoring iterations: 6
confint(TMTAlog3)
## 2.5 % 97.5 %
## (Intercept) -3.72730583 1.48515517
## TrailsA -0.02354824 0.01075608
## SexMen -0.97314538 1.46060644
## Age -0.06559716 0.00527444
## WRATtotal -0.03396644 0.05475529
## TrailsA:SexMen -0.05005641 0.02032774
exp(cbind(OR = coef(TMTAlog3), confint(TMTAlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 0.3415636 0.02405756 4.415651
## TrailsA 0.9998258 0.97672685 1.010814
## SexMen 1.1052316 0.37789255 4.308572
## Age 0.9707813 0.93650805 1.005288
## WRATtotal 1.0090483 0.96660394 1.056282
## TrailsA:SexMen 0.9915264 0.95117577 1.020536
##Plots
plot(predictorEffect("TrailsA",TMTAlog3))
Dissertation Analyses for Below Poverty Status Only
Trail Making Test Part A - Psychological Aggression
Model 1
TMTAlog1 <- glm(PsychAggress ~ TrailsA + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(TMTAlog1)
##
## Call:
## glm(formula = PsychAggress ~ TrailsA + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2647 0.4142 0.4504 0.4919 0.7646
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.374233 1.217421 1.129 0.259
## TrailsA -0.010943 0.007194 -1.521 0.128
## WRATtotal 0.027453 0.028223 0.973 0.331
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 135.38 on 198 degrees of freedom
## AIC: 141.38
##
## Number of Fisher Scoring iterations: 5
confint(TMTAlog1)
## 2.5 % 97.5 %
## (Intercept) -0.91116570 3.919603591
## TrailsA -0.02922441 0.003631947
## WRATtotal -0.03005160 0.081824090
exp(cbind(OR = coef(TMTAlog1), confint(TMTAlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 3.9520436 0.4020553 50.380470
## TrailsA 0.9891167 0.9711985 1.003639
## WRATtotal 1.0278334 0.9703955 1.085265
#Plots
plot(predictorEffect("TrailsA",TMTAlog1))
Model 3
TMTAlog3 <- glm(PsychAggress ~ (TrailsA + Sex)^2 + Age + WRATtotal, data = AllvarsBelow,family = "binomial")
summary(TMTAlog3)
##
## Call:
## glm(formula = PsychAggress ~ (TrailsA + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3555 0.4077 0.4526 0.4836 0.7682
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.339088 1.827805 0.186 0.853
## TrailsA 0.001425 0.024599 0.058 0.954
## SexMen 0.367246 0.988110 0.372 0.710
## Age 0.015088 0.026943 0.560 0.575
## WRATtotal 0.027821 0.028601 0.973 0.331
## TrailsA:SexMen -0.013850 0.026246 -0.528 0.598
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 134.57 on 195 degrees of freedom
## AIC: 146.57
##
## Number of Fisher Scoring iterations: 5
confint(TMTAlog3)
## 2.5 % 97.5 %
## (Intercept) -3.27485622 3.95473969
## TrailsA -0.03875560 0.06118787
## SexMen -1.44992009 2.49289961
## Age -0.03722866 0.06927010
## WRATtotal -0.03010322 0.08325467
## TrailsA:SexMen -0.07637437 0.02982834
exp(cbind(OR = coef(TMTAlog3), confint(TMTAlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 1.403667 0.03782231 52.182108
## TrailsA 1.001426 0.96198579 1.063099
## SexMen 1.443752 0.23458903 12.096300
## Age 1.015202 0.96345580 1.071726
## WRATtotal 1.028212 0.97034537 1.086819
## TrailsA:SexMen 0.986245 0.92646930 1.030278
##Plots
plot(predictorEffect("TrailsA",TMTAlog3))
Trail Making Test Part A - Physical Assault
Model 1
TMTAlog1 <- glm(PhysAssault ~ TrailsA + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(TMTAlog1)
##
## Call:
## glm(formula = PhysAssault ~ TrailsA + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7857 -0.6575 -0.5837 -0.4567 2.1998
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.82119 1.39270 -1.308 0.191
## TrailsA -0.02388 0.01756 -1.360 0.174
## WRATtotal 0.02372 0.02789 0.851 0.395
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 182.73 on 200 degrees of freedom
## Residual deviance: 179.03 on 198 degrees of freedom
## AIC: 185.03
##
## Number of Fisher Scoring iterations: 5
confint(TMTAlog1)
## 2.5 % 97.5 %
## (Intercept) -4.62362452 0.868176639
## TrailsA -0.06134589 0.003966274
## WRATtotal -0.02919876 0.080755163
exp(cbind(OR = coef(TMTAlog1), confint(TMTAlog1)))
## OR 2.5 % 97.5 %
## (Intercept) 0.1618323 0.009817149 2.382563
## TrailsA 0.9764017 0.940497874 1.003974
## WRATtotal 1.0240051 0.971223408 1.084105
##Plots
plot(predictorEffect("TrailsA",TMTAlog1))
Model 3
TMTAlog3 <- glm(PhysAssault ~ (TrailsA + Sex)^2+ Age + WRATtotal, data = AllvarsBelow,family = "binomial")
summary(TMTAlog3)
##
## Call:
## glm(formula = PhysAssault ~ (TrailsA + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.0064 -0.6644 -0.5464 -0.4044 2.1531
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.12444 1.69889 -0.073 0.942
## TrailsA -0.04062 0.02910 -1.396 0.163
## SexMen -1.11362 1.01236 -1.100 0.271
## Age -0.02900 0.02278 -1.273 0.203
## WRATtotal 0.02428 0.02763 0.879 0.380
## TrailsA:SexMen 0.03573 0.03170 1.127 0.260
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 182.73 on 200 degrees of freedom
## Residual deviance: 175.71 on 195 degrees of freedom
## AIC: 187.71
##
## Number of Fisher Scoring iterations: 5
confint(TMTAlog3)
## 2.5 % 97.5 %
## (Intercept) -3.48707129 3.215065236
## TrailsA -0.10522393 0.007676091
## SexMen -3.14471339 0.984567664
## Age -0.07488326 0.014971179
## WRATtotal -0.02805941 0.080943339
## TrailsA:SexMen -0.02738174 0.103401460
exp(cbind(OR = coef(TMTAlog3), confint(TMTAlog3)))
## OR 2.5 % 97.5 %
## (Intercept) 0.8829879 0.03059033 24.904917
## TrailsA 0.9601965 0.90012294 1.007706
## SexMen 0.3283693 0.04307927 2.676654
## Age 0.9714196 0.92785180 1.015084
## WRATtotal 1.0245813 0.97233060 1.084309
## TrailsA:SexMen 1.0363741 0.97298974 1.108937
##Plots
plot(predictorEffect("TrailsA",TMTAlog3))
