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

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

## ----eval=FALSE---------------------------------------------------------------
#  intensive <- rep(0,length(Intensive))
#  intensive[Intensive>0] <- 1
#  Intensive <- intensive
#  
#  previous <- Previous
#  previous[previous>1] <- 2
#  Previous <- previous

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

## ----eval=FALSE---------------------------------------------------------------
#  library(VGAM)
#  Birth <- as.data.frame(na.omit(cbind(Intensive, Cesarean, Sex, Weight, Previous,
#  AgeMother)))
#  detach(birth)
#  bivarlogit <- vglm(cbind(Intensive , Cesarean) ~ Weight + AgeMother +
#  as.factor(Sex) + as.factor(Previous), binom2.or(zero=NULL), data=Birth)
#  summary(bivarlogit)

## ----eval=FALSE---------------------------------------------------------------
#  n <- dim(Birth)[1]
#  ID <- rep(1:n,2)
#  
#  InterceptInt <- InterceptCes <- rep(1, 2*n)
#  InterceptInt[(n+1):(2*n)] <- InterceptCes[1:n] <- 0
#  
#  AgeMotherInt <- AgeMotherCes <- rep(Birth$AgeMother,2)
#  AgeMotherInt[(n+1):(2*n)] <- AgeMotherCes[1:n] <- 0
#  
#  SexInt <- SexCes <- rep(Birth$Sex,2)
#  SexInt[SexInt==1] <- SexCes[SexCes==1] <- 0
#  SexInt[SexInt==2] <- SexCes[SexCes==2] <- 1
#  SexInt[(n+1):(2*n)] <- SexCes[1:n] <- 0
#  
#  PrevBase <- rep(Birth$Previous,2)
#  PreviousInt1 <- PreviousCes1 <- PreviousInt2 <- PreviousCes2 <- rep(0, 2*n)
#  PreviousInt1[PrevBase==1] <- PreviousCes1[PrevBase==1] <- 1
#  PreviousInt2[PrevBase>=2] <- PreviousCes2[PrevBase>=2] <- 1
#  PreviousInt1[(n+1):(2*n)] <- PreviousInt2[(n+1):(2*n)] <- PreviousCes1[1:n] <-
#    PreviousCes2[1:n] <- 0
#  
#  WeightInt <- WeightCes <- rep(Birth$Weight,2)
#  WeightInt[(n+1):(2*n)] <- WeightCes[1:n] <- 0

## ----eval=FALSE---------------------------------------------------------------
#  GeeDat <- as.data.frame(cbind(ID, InterceptInt, InterceptCes, SexInt , SexCes ,
#  WeightInt , WeightCes , PreviousInt1 , PreviousInt2, PreviousCes1,
#  PreviousCes2, AgeMotherInt , AgeMotherCes, Response=
#  c(Birth$Intensive, Birth$Cesarean)))

## ----eval=FALSE---------------------------------------------------------------
#  gee1 <- gee (Response ~ -1 + InterceptInt + InterceptCes + WeightInt + WeightCes
#               + AgeMotherInt + AgeMotherCes + SexInt + SexCes +
#  PreviousInt1 + PreviousCes1 + PreviousInt2 + PreviousCes2,
#  family=binomial(link=logit), id=ID, data=GeeDat)
#  
#  summary(gee1)

## ----eval=FALSE---------------------------------------------------------------
#  coefficients(bivarlogit)[1:2]
#  coefficients(gee1)[1:2]
#  
#  coefficients(bivarlogit)[4:5]
#  coefficients(gee1)[3:4]
#  
#  coefficients(bivarlogit)[7:8]
#  coefficients(gee1)[5:6]
#  
#  coefficients(bivarlogit)[10:11]
#  coefficients(gee1)[7:8]
#  
#  coefficients(bivarlogit)[13:14]
#  coefficients(gee1)[9:10]
#  
#  coefficients(bivarlogit)[16:17]
#  coefficients(gee1)[11:12]

## ----echo=FALSE,eval=FALSE----------------------------------------------------
#  detach(package:VGAM)