“CVLT Above “Poverty Vs. Below Poverty”
Dissertation Analyses with ABOVE poverty only
load(file="/Users/meganwilliams/Desktop/Dissertation/AllvarsAbove.rdata")
load(file="/Users/meganwilliams/Desktop/Dissertation/AllvarsBelow.rdata")
library(effects)
library(interactions)
library(car)
library(rcompanion)California Verbal Learning Test (Total Correct Trial A) - Psychological Aggression
Model 1
CVLTlog1 <- glm(PsychAggress ~ CVLtca + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PsychAggress ~ CVLtca + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2682 0.4410 0.5192 0.5908 0.8676
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.569417 0.765511 0.744 0.4570
## CVLtca 0.045134 0.018102 2.493 0.0127 *
## WRATtotal 0.007628 0.018180 0.420 0.6748
## ---
## 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: 357.05 on 437 degrees of freedom
## AIC: 363.05
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PsychAggress ~ (CVLtca+ Sex)^2 + Age + WRATtotal, data = AllvarsAbove, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PsychAggress ~ (CVLtca + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3743 0.3908 0.4974 0.6121 0.9931
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.3425777 1.1845640 1.978 0.0480 *
## CVLtca 0.0329625 0.0276946 1.190 0.2340
## SexMen -0.4530255 0.7222164 -0.627 0.5305
## Age -0.0309024 0.0158556 -1.949 0.0513 .
## WRATtotal 0.0123918 0.0182173 0.680 0.4964
## CVLtca:SexMen 0.0007613 0.0359432 0.021 0.9831
## ---
## 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: 350.63 on 434 degrees of freedom
## AIC: 362.63
##
## Number of Fisher Scoring iterations: 5plot(allEffects(CVLTlog3))
# California Verbal Learning Test (Total Correct Trial A) - Physical Assault
Model 1
CVLTlog1 <- glm(PhysAssault ~ CVLtca + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PhysAssault ~ CVLtca + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.5796 -0.4892 -0.4590 -0.4320 2.3069
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.818964 0.980504 -2.875 0.00404 **
## CVLtca 0.018953 0.021210 0.894 0.37154
## WRATtotal 0.006229 0.022748 0.274 0.78422
## ---
## 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: 293.58 on 437 degrees of freedom
## AIC: 299.58
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PhysAssault ~ (CVLtca+ Sex)^2 + Age + WRATtotal, data = AllvarsAbove, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PhysAssault ~ (CVLtca + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7226 -0.5031 -0.4457 -0.3885 2.3330
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.486627 1.403384 -1.059 0.289
## CVLtca 0.018580 0.029036 0.640 0.522
## SexMen 0.340582 0.906276 0.376 0.707
## Age -0.029445 0.018039 -1.632 0.103
## WRATtotal 0.008575 0.023284 0.368 0.713
## CVLtca:SexMen -0.023791 0.040248 -0.591 0.554
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 294.76 on 439 degrees of freedom
## Residual deviance: 290.26 on 434 degrees of freedom
## AIC: 302.26
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Long Delayed Free Recall) - Psychological Aggression
Model 1
CVLTlog1 <- glm(PsychAggress ~ CVLfrl + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PsychAggress ~ CVLfrl + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4003 0.4209 0.5199 0.6068 0.7869
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.742408 0.760634 0.976 0.3290
## CVLfrl 0.113331 0.043699 2.593 0.0095 **
## WRATtotal 0.009687 0.017763 0.545 0.5855
## ---
## 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: 356.31 on 437 degrees of freedom
## AIC: 362.31
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PsychAggress ~ (CVLfrl+ Sex)^2 + Age + WRATtotal, data = AllvarsAbove, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PsychAggress ~ (CVLfrl + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4504 0.3865 0.4966 0.6068 0.9344
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.47538 1.15102 2.151 0.0315 *
## CVLfrl 0.07398 0.06562 1.127 0.2596
## SexMen -0.53086 0.52325 -1.015 0.3103
## Age -0.02972 0.01586 -1.873 0.0610 .
## WRATtotal 0.01343 0.01789 0.750 0.4530
## CVLfrl:SexMen 0.01987 0.08817 0.225 0.8217
## ---
## 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: 350.26 on 434 degrees of freedom
## AIC: 362.26
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Long Delayed Free Recall) - Physical Assault
Model 1
CVLTlog1 <- glm(PhysAssault ~ CVLfrl + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PhysAssault ~ CVLfrl + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6363 -0.4950 -0.4512 -0.4086 2.3173
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.707485 0.973345 -2.782 0.00541 **
## CVLfrl 0.072661 0.047440 1.532 0.12562
## WRATtotal 0.002516 0.022625 0.111 0.91144
## ---
## 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: 292.02 on 437 degrees of freedom
## AIC: 298.02
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PhysAssault ~ (CVLfrl+ Sex)^2 + Age + WRATtotal, data = AllvarsAbove, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PhysAssault ~ (CVLfrl + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7630 -0.5032 -0.4405 -0.3858 2.3471
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.52577 1.35802 -1.124 0.261
## CVLfrl 0.07042 0.06478 1.087 0.277
## SexMen 0.18718 0.66620 0.281 0.779
## Age -0.02616 0.01812 -1.444 0.149
## WRATtotal 0.00452 0.02301 0.196 0.844
## CVLfrl:SexMen -0.04843 0.09133 -0.530 0.596
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 294.76 on 439 degrees of freedom
## Residual deviance: 289.49 on 434 degrees of freedom
## AIC: 301.49
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Short Delayed Free Recall) - Psychological Aggression
Model 1
CVLTlog1 <- glm(PsychAggress ~ CVLfrs + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PsychAggress ~ CVLfrs + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3156 0.4519 0.5293 0.6016 0.8042
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.75276 0.75622 0.995 0.3195
## CVLfrs 0.08828 0.04281 2.062 0.0392 *
## WRATtotal 0.01218 0.01774 0.687 0.4922
## ---
## 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: 358.95 on 437 degrees of freedom
## AIC: 364.95
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog1))
## Model 3
CVLTlog3 <- glm(PsychAggress ~ (CVLfrs+ Sex)^2 + Age + WRATtotal, data = AllvarsAbove, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PsychAggress ~ (CVLfrs + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4678 0.3990 0.5008 0.6064 0.9031
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.531784 1.138140 2.224 0.0261 *
## CVLfrs 0.056237 0.065400 0.860 0.3898
## SexMen -0.489336 0.530495 -0.922 0.3563
## Age -0.031403 0.015934 -1.971 0.0488 *
## WRATtotal 0.016390 0.017816 0.920 0.3576
## CVLfrs:SexMen 0.004025 0.086054 0.047 0.9627
## ---
## 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: 352.00 on 434 degrees of freedom
## AIC: 364
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Short Delayed Free Recall) - Physical Assault
Model 1
CVLTlog1 <- glm(PhysAssault ~ CVLfrs + WRATtotal, data=AllvarsAbove,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PhysAssault ~ CVLfrs + WRATtotal, family = "binomial",
## data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.6111 -0.4998 -0.4531 -0.4104 2.3138
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.732895 0.975864 -2.800 0.0051 **
## CVLfrs 0.069568 0.047768 1.456 0.1453
## WRATtotal 0.003442 0.022561 0.153 0.8787
## ---
## 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: 292.24 on 437 degrees of freedom
## AIC: 298.24
##
## Number of Fisher Scoring iterations: 5#Plots
plot(predictorEffect("CVLfrs",CVLTlog1))
Model 3
CVLTlog3 <- glm(PhysAssault ~ (CVLfrs+ Sex)^2 + Age + WRATtotal, data = AllvarsAbove, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PhysAssault ~ (CVLfrs + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsAbove)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7829 -0.4950 -0.4378 -0.3848 2.4051
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.61622 1.36403 -1.185 0.236
## CVLfrs 0.08683 0.06546 1.326 0.185
## SexMen 0.44674 0.67518 0.662 0.508
## Age -0.02697 0.01812 -1.489 0.137
## WRATtotal 0.00486 0.02294 0.212 0.832
## CVLfrs:SexMen -0.09116 0.09247 -0.986 0.324
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 294.76 on 439 degrees of freedom
## Residual deviance: 288.90 on 434 degrees of freedom
## AIC: 300.9
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog3))
interact_plot(model = CVLTlog3, pred = CVLfrs, modx = Sex)
sim_slopes(CVLTlog3, pred = CVLfrs, modx = Sex, centered = "all",jnplot = TRUE)## Warning: Johnson-Neyman intervals are not available for factor moderators.## SIMPLE SLOPES ANALYSIS
##
## Slope of CVLfrs when Sex = Men:
##
## Est. S.E. z val. p
## ------- ------ -------- ------
## -0.00 0.07 -0.06 0.95
##
## Slope of CVLfrs when Sex = Women:
##
## Est. S.E. z val. p
## ------ ------ -------- ------
## 0.09 0.07 1.33 0.18Dissertation Analyses with BELOW poverty only
California Verbal Learning Test (Total Correct Trial A) - Psychological Aggression
Model 1
CVLTlog1 <- glm(PsychAggress ~ CVLtca + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PsychAggress ~ CVLtca + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.2673 0.4235 0.4614 0.5056 0.6954
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.91828 1.18352 0.776 0.438
## CVLtca -0.01284 0.02924 -0.439 0.661
## WRATtotal 0.03436 0.02964 1.159 0.246
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 137.52 on 198 degrees of freedom
## AIC: 143.52
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PsychAggress ~ (CVLtca+ Sex)^2 + Age + WRATtotal, data = AllvarsBelow, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PsychAggress ~ (CVLtca + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3394 0.4061 0.4595 0.5064 0.7244
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.276875 1.912048 0.145 0.885
## CVLtca -0.009534 0.040709 -0.234 0.815
## SexMen -0.106957 1.196148 -0.089 0.929
## Age 0.016335 0.026950 0.606 0.544
## WRATtotal 0.033866 0.029523 1.147 0.251
## CVLtca:SexMen -0.008788 0.059301 -0.148 0.882
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 136.83 on 195 degrees of freedom
## AIC: 148.83
##
## Number of Fisher Scoring iterations: 5plot(allEffects(CVLTlog3))
# California Verbal Learning Test (Total Correct Trial A) - Physical Assault
Model 1
CVLTlog1 <- glm(PhysAssault ~ CVLtca + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PhysAssault ~ CVLtca + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7292 -0.6421 -0.5960 -0.5212 2.1066
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.90150 1.18870 -2.441 0.0147 *
## CVLtca 0.01012 0.02408 0.420 0.6743
## WRATtotal 0.02632 0.02778 0.947 0.3435
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 182.73 on 200 degrees of freedom
## Residual deviance: 181.32 on 198 degrees of freedom
## AIC: 187.32
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PhysAssault ~ (CVLtca+ Sex)^2 + Age + WRATtotal, data = AllvarsBelow, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PhysAssault ~ (CVLtca + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.9000 -0.6539 -0.5612 -0.4375 2.1442
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.52191 1.67744 -0.311 0.7557
## CVLtca -0.02242 0.03124 -0.718 0.4729
## SexMen -1.27295 1.05422 -1.207 0.2272
## Age -0.03792 0.02277 -1.665 0.0958 .
## WRATtotal 0.02551 0.02830 0.901 0.3674
## CVLtca:SexMen 0.06326 0.05215 1.213 0.2251
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 182.73 on 200 degrees of freedom
## Residual deviance: 176.93 on 195 degrees of freedom
## AIC: 188.93
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Long Delayed Free Recall) - Psychological Aggression
Model 1
CVLTlog1 <- glm(PsychAggress ~ CVLfrl + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PsychAggress ~ CVLfrl + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4434 0.3578 0.4502 0.5184 0.7398
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.73185 1.17374 0.624 0.5329
## CVLfrl 0.12423 0.07527 1.651 0.0988 .
## WRATtotal 0.01844 0.02899 0.636 0.5246
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 134.89 on 198 degrees of freedom
## AIC: 140.89
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PsychAggress ~ (CVLfrl+ Sex)^2 + Age + WRATtotal, data = AllvarsBelow, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PsychAggress ~ (CVLfrl + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.5186 0.3419 0.4265 0.5325 0.8206
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.83371 1.86750 -0.446 0.655
## CVLfrl 0.14211 0.10523 1.350 0.177
## SexMen -0.15128 0.81191 -0.186 0.852
## Age 0.03429 0.02750 1.247 0.212
## WRATtotal 0.01814 0.02938 0.618 0.537
## CVLfrl:SexMen 0.03051 0.15570 0.196 0.845
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 133.27 on 195 degrees of freedom
## AIC: 145.27
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Long Delayed Free Recall) - Physical Assault
Model 1
CVLTlog1 <- glm(PhysAssault ~ CVLfrl + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PhysAssault ~ CVLfrl + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.7444 -0.6407 -0.5953 -0.5233 2.1386
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.80966 1.17376 -2.394 0.0167 *
## CVLfrl -0.02692 0.05866 -0.459 0.6463
## WRATtotal 0.03208 0.02766 1.160 0.2462
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 182.73 on 200 degrees of freedom
## Residual deviance: 181.28 on 198 degrees of freedom
## AIC: 187.28
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog1))
Model 3
CVLTlog3 <- glm(PhysAssault ~ (CVLfrl+ Sex)^2 + Age + WRATtotal, data = AllvarsBelow, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PhysAssault ~ (CVLfrl + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.0049 -0.6387 -0.5181 -0.3858 2.1749
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.19316 1.67095 0.116 0.9080
## CVLfrl -0.16839 0.08335 -2.020 0.0433 *
## SexMen -1.50028 0.77978 -1.924 0.0544 .
## Age -0.04475 0.02324 -1.925 0.0542 .
## WRATtotal 0.02768 0.02851 0.971 0.3317
## CVLfrl:SexMen 0.24968 0.12567 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: 182.73 on 200 degrees of freedom
## Residual deviance: 173.20 on 195 degrees of freedom
## AIC: 185.2
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Short Delayed Free Recall) - Psychological Aggression
Model 1
CVLTlog1 <- glm(PsychAggress ~ CVLfrs + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PsychAggress ~ CVLfrs + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.3371 0.4044 0.4552 0.5180 0.7467
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.82216 1.17052 0.702 0.482
## CVLfrs 0.06801 0.07692 0.884 0.377
## WRATtotal 0.02233 0.02964 0.753 0.451
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 136.93 on 198 degrees of freedom
## AIC: 142.93
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog1))
## Model 3
CVLTlog3 <- glm(PsychAggress ~ (CVLfrs+ Sex)^2 + Age + WRATtotal, data = AllvarsBelow, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PsychAggress ~ (CVLfrs + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.4362 0.3778 0.4486 0.5047 0.8287
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.10442 1.83295 0.057 0.955
## CVLfrs 0.02889 0.10307 0.280 0.779
## SexMen -0.74874 0.87410 -0.857 0.392
## Age 0.02557 0.02708 0.944 0.345
## WRATtotal 0.01972 0.02978 0.662 0.508
## CVLfrs:SexMen 0.12553 0.15333 0.819 0.413
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 138.84 on 200 degrees of freedom
## Residual deviance: 135.29 on 195 degrees of freedom
## AIC: 147.29
##
## Number of Fisher Scoring iterations: 5#Plots
plot(allEffects(CVLTlog3))
California Verbal Learning Test (Short Delayed Free Recall) - Physical Assault
Model 1
CVLTlog1 <- glm(PhysAssault ~ CVLfrs + WRATtotal, data=AllvarsBelow,family = "binomial")
summary(CVLTlog1)##
## Call:
## glm(formula = PhysAssault ~ CVLfrs + WRATtotal, family = "binomial",
## data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.8317 -0.6331 -0.5689 -0.4919 2.2313
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.83417 1.17905 -2.404 0.0162 *
## CVLfrs -0.07762 0.06309 -1.230 0.2185
## WRATtotal 0.03901 0.02822 1.382 0.1668
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 182.73 on 200 degrees of freedom
## Residual deviance: 179.96 on 198 degrees of freedom
## AIC: 185.96
##
## Number of Fisher Scoring iterations: 4#Plots
plot(predictorEffect("CVLfrs",CVLTlog1))
Model 3
CVLTlog3 <- glm(PhysAssault ~ (CVLfrs+ Sex)^2 + Age + WRATtotal, data = AllvarsBelow, family = "binomial")
summary(CVLTlog3)##
## Call:
## glm(formula = PhysAssault ~ (CVLfrs + Sex)^2 + Age + WRATtotal,
## family = "binomial", data = AllvarsBelow)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.1084 -0.6542 -0.4930 -0.3764 2.2062
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.06716 1.66175 0.040 0.9678
## CVLfrs -0.21219 0.08705 -2.438 0.0148 *
## SexMen -1.44714 0.78934 -1.833 0.0668 .
## Age -0.04602 0.02316 -1.987 0.0469 *
## WRATtotal 0.03678 0.02946 1.248 0.2119
## CVLfrs:SexMen 0.24123 0.13008 1.854 0.0637 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 182.73 on 200 degrees of freedom
## Residual deviance: 171.81 on 195 degrees of freedom
## AIC: 183.81
##
## Number of Fisher Scoring iterations: 4#Plots
plot(allEffects(CVLTlog3))
interact_plot(model = CVLTlog3, pred = CVLfrs, modx = Sex)
sim_slopes(CVLTlog3, pred = CVLfrs, modx = Sex, centered = "all",jnplot = TRUE)## Warning: Johnson-Neyman intervals are not available for factor moderators.## SIMPLE SLOPES ANALYSIS
##
## Slope of CVLfrs when Sex = Men:
##
## Est. S.E. z val. p
## ------ ------ -------- ------
## 0.03 0.10 0.28 0.78
##
## Slope of CVLfrs when Sex = Women:
##
## Est. S.E. z val. p
## ------- ------ -------- ------
## -0.21 0.09 -2.44 0.01