library(effects) ## load the effects package
library(car) ## for Anova: type II tests
data(Cowles, package = "carData")
Main effects model
mod.cowles0 <- glm(volunteer ~ sex + neuroticism + extraversion,
data=Cowles, family=binomial)
summary(mod.cowles0)
##
## Call:
## glm(formula = volunteer ~ sex + neuroticism + extraversion, family = binomial,
## data = Cowles)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.3977 -1.0454 -0.9084 1.2601 1.6849
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -1.116496 0.249057 -4.483 7.36e-06 ***
## sexmale -0.235161 0.111185 -2.115 0.0344 *
## neuroticism 0.006362 0.011357 0.560 0.5754
## extraversion 0.066325 0.014260 4.651 3.30e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1933.5 on 1420 degrees of freedom
## Residual deviance: 1906.1 on 1417 degrees of freedom
## AIC: 1914.1
##
## Number of Fisher Scoring iterations: 4
Anova(mod.cowles0)
## Analysis of Deviance Table (Type II tests)
##
## Response: volunteer
## LR Chisq Df Pr(>Chisq)
## sex 4.4861 1 0.03417 *
## neuroticism 0.3139 1 0.57532
## extraversion 22.1372 1 2.538e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Test all interactions
mod.cowles1 <- glm(volunteer ~ (sex + neuroticism + extraversion)^2,
data=Cowles, family=binomial)
summary(mod.cowles1)
##
## Call:
## glm(formula = volunteer ~ (sex + neuroticism + extraversion)^2,
## family = binomial, data = Cowles)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.4981 -1.0545 -0.8958 1.2597 1.9670
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.498183 0.575546 -4.341 1.42e-05 ***
## sexmale -0.021976 0.491866 -0.045 0.96436
## neuroticism 0.115450 0.039370 2.932 0.00336 **
## extraversion 0.176503 0.042725 4.131 3.61e-05 ***
## sexmale:neuroticism -0.003680 0.023020 -0.160 0.87300
## sexmale:extraversion -0.014661 0.029381 -0.499 0.61778
## neuroticism:extraversion -0.008809 0.002987 -2.949 0.00319 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1933.5 on 1420 degrees of freedom
## Residual deviance: 1897.2 on 1414 degrees of freedom
## AIC: 1911.2
##
## Number of Fisher Scoring iterations: 4
Anova(mod.cowles1)
## Analysis of Deviance Table (Type II tests)
##
## Response: volunteer
## LR Chisq Df Pr(>Chisq)
## sex 4.9184 1 0.026572 *
## neuroticism 0.3150 1 0.574642
## extraversion 22.1016 1 2.586e-06 ***
## sex:neuroticism 0.0256 1 0.873001
## sex:extraversion 0.2491 1 0.617718
## neuroticism:extraversion 8.8117 1 0.002993 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Add one interaction
mod.cowles <- glm(volunteer ~ sex + neuroticism * extraversion,
data=Cowles, family=binomial)
summary(mod.cowles)
##
## Call:
## glm(formula = volunteer ~ sex + neuroticism * extraversion, family = binomial,
## data = Cowles)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.4749 -1.0602 -0.8934 1.2609 1.9978
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.358207 0.501320 -4.704 2.55e-06 ***
## sexmale -0.247152 0.111631 -2.214 0.02683 *
## neuroticism 0.110777 0.037648 2.942 0.00326 **
## extraversion 0.166816 0.037719 4.423 9.75e-06 ***
## neuroticism:extraversion -0.008552 0.002934 -2.915 0.00355 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 1933.5 on 1420 degrees of freedom
## Residual deviance: 1897.4 on 1416 degrees of freedom
## AIC: 1907.4
##
## Number of Fisher Scoring iterations: 4
anova(mod.cowles0, mod.cowles, mod.cowles1)
## Analysis of Deviance Table
##
## Model 1: volunteer ~ sex + neuroticism + extraversion
## Model 2: volunteer ~ sex + neuroticism * extraversion
## Model 3: volunteer ~ (sex + neuroticism + extraversion)^2
## Resid. Df Resid. Dev Df Deviance
## 1 1417 1906.1
## 2 1416 1897.4 1 8.6213
## 3 1414 1897.2 2 0.2579
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