Output from arthritis-diag.R

library(vcd)
# main effects model
data(Arthritis)
# define Better
Arthritis$Better <- Arthritis$Improved > "None"
arth.mod1 <- glm(Better ~ Age + Sex + Treatment, data = Arthritis, family = "binomial")
Anova(arth.mod1)

## Analysis of Deviance Table (Type II tests)
## 
## Response: Better
##           LR Chisq Df Pr(>Chisq)    
## Age           6.16  1    0.01308 *  
## Sex           6.98  1    0.00823 ** 
## Treatment    12.20  1    0.00048 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

# diagnostic plots: 'regression quartet' setwd('c:/sasuser/catdata/R')
# postscript(file='arthritis-diag1.eps', paper='special', height=6, width=6,
# onefile=TRUE, horizontal=FALSE)
op <- par(mfrow = c(2, 2))
plot(arth.mod1)

par(op)
# dev.off()

library(car)
# influence plot postscript(file='arthritis-diag2.eps', paper='special', height=6,
# width=6, onefile=TRUE, horizontal=FALSE)
influencePlot(arth.mod1, main = "Arthritis data: influencePlot")

# dev.off()