## Mental health data
library(gnm)
library(vcdExtra)
data(Mental)
# display the frequency table
(Mental.tab <- xtabs(Freq ~ mental+ses, data=Mental))
## ses
## mental 1 2 3 4 5 6
## Well 64 57 57 72 36 21
## Mild 94 94 105 141 97 71
## Moderate 58 54 65 77 54 54
## Impaired 46 40 60 94 78 71
# Residual deviance: 47.418 on 15 degrees of freedom
indep <- glm(Freq ~ mental+ses,
family = poisson, data = Mental)
deviance(indep)
## [1] 47.41785
long.labels <- list(set_varnames = c(mental="Mental Health Status", ses="Parent SES"))
mosaic(indep,residuals_type="rstandard", labeling_args = long.labels, labeling=labeling_residuals,
main="Mental health data: Independence")
# as a sieve diagram
mosaic(indep, labeling_args = long.labels, panel=sieve, gp=shading_Friendly,
main="Mental health data: Independence")
Use integer scores for rows/cols
Cscore <- as.numeric(Mental$ses)
Rscore <- as.numeric(Mental$mental)
coleff <- glm(Freq ~ mental + ses + Rscore:ses,
family = poisson, data = Mental)
mosaic(coleff,residuals_type="rstandard",
labeling_args = long.labels, labeling=labeling_residuals, suppress=1, gp=shading_Friendly,
main="Mental health data: Col effects (ses)")
roweff <- glm(Freq ~ mental + ses + mental:Cscore,
family = poisson, data = Mental)
mosaic(roweff,residuals_type="rstandard",
labeling_args = long.labels, labeling=labeling_residuals, suppress=1, gp=shading_Friendly,
main="Mental health data: Row effects (mental)")
linlin <- glm(Freq ~ mental + ses + Rscore:Cscore,
family = poisson, data = Mental)
# compare models
anova(indep, roweff, coleff, linlin)
## Analysis of Deviance Table
##
## Model 1: Freq ~ mental + ses
## Model 2: Freq ~ mental + ses + mental:Cscore
## Model 3: Freq ~ mental + ses + Rscore:ses
## Model 4: Freq ~ mental + ses + Rscore:Cscore
## Resid. Df Resid. Dev Df Deviance
## 1 15 47.418
## 2 12 6.281 3 41.137
## 3 10 6.829 2 -0.549
## 4 14 9.895 -4 -3.066
AIC(indep, roweff, coleff, linlin)
## df AIC
## indep 9 209.5908
## roweff 12 174.4537
## coleff 14 179.0023
## linlin 10 174.0681
mosaic(linlin,residuals_type="rstandard",
labeling_args = long.labels, labeling=labeling_residuals, suppress=1, gp=shading_Friendly,
main="Mental health data: Linear x Linear")
Mental$mental <- C(Mental$mental, treatment)
Mental$ses <- C(Mental$ses, treatment)
RC1model <- gnm(Freq ~ mental + ses + Mult(mental, ses),
family = poisson, data = Mental)
## Initialising
## Running start-up iterations..
## Running main iterations........
## Done
mosaic(RC1model, residuals_type="rstandard",
labeling_args = long.labels, labeling=labeling_residuals, suppress=1, gp=shading_Friendly,
main="Mental health data: RC(1) model")