## ----echo=FALSE,eval=FALSE----------------------------------------------------
# options(width=80)

## ----results='hide',eval=FALSE------------------------------------------------
# library(catdata)
# data(knee)
# attach(knee)

## ----eval=FALSE---------------------------------------------------------------
# R2D <- rep(0, length(R2))
# R3D <- rep(0, length(R3))
# R4D <- rep(0, length(R3))
# 
# R2D[R2>2] <- 1
# R3D[R3>2] <- 1
# R4D[R4>2] <- 1

## ----eval=FALSE---------------------------------------------------------------
# N <- rep(knee$N, each=3)
# Th <- rep(knee$Th, each=3)
# Age <- rep(knee$Age, each=3)
# Sex <- rep(knee$Sex, each=3)

## ----eval=FALSE---------------------------------------------------------------
# Response <- c(rbind(R2D,R3D,R4D))
# Age2 <- Age^2

## ----eval=FALSE---------------------------------------------------------------
# Th <- as.factor(Th)
# Sex <- as.factor(Sex)

## ----eval=FALSE---------------------------------------------------------------
# library(gee)

## ----results='hide',eval=FALSE------------------------------------------------
# gee1a <- gee(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit))

## ----eval=FALSE---------------------------------------------------------------
# summary(gee1a)

## ----results='hide',eval=FALSE------------------------------------------------
# gee2a <- gee(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit), corstr="exchangeable")

## ----eval=FALSE---------------------------------------------------------------
# summary(gee2a)

## ----results='hide',eval=FALSE------------------------------------------------
# gee3a <- gee(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit), corstr="AR-M", Mv=1)

## ----eval=FALSE---------------------------------------------------------------
# summary(gee3a)

## ----eval=FALSE---------------------------------------------------------------
# library(geepack)

## ----results='hide',eval=FALSE------------------------------------------------
# gee1b <- geeglm(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit))

## ----eval=FALSE---------------------------------------------------------------
# summary(gee1b)

## ----results='hide',eval=FALSE------------------------------------------------
# gee2b <- geeglm(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit), corstr="exchangeable")

## ----eval=FALSE---------------------------------------------------------------
# summary(gee2b)

## ----results='hide',eval=FALSE------------------------------------------------
# gee3b <- geeglm(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit), corstr="ar1")

## ----eval=FALSE---------------------------------------------------------------
# summary(gee3b)

## ----eval=FALSE---------------------------------------------------------------
# glm1 <- glm(Response ~ Th + Sex + Age + Age2,
# family=binomial(link=logit))
# summary(glm1)

## ----eval=FALSE---------------------------------------------------------------
# Age <- Age-30
# Age2 <- Age^2

## ----results='hide',eval=FALSE------------------------------------------------
# gee1c <- gee(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit))

## ----eval=FALSE---------------------------------------------------------------
# summary(gee1c)

## ----results='hide',eval=FALSE------------------------------------------------
# gee2c <- gee(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit), corstr="exchangeable")

## ----eval=FALSE---------------------------------------------------------------
# summary(gee2c)

## ----results='hide',eval=FALSE------------------------------------------------
# gee3c <- gee(Response ~ Th + Sex + Age + Age2, id=N,
# family=binomial(link=logit), corstr="AR-M", Mv=1)

## ----eval=FALSE---------------------------------------------------------------
# summary(gee3c)