## ----echo=FALSE------------------------------------------- options(width=60) ## ----results="hide",eval = TRUE--------------------------- library(catdata) data(teratology) data(teratology2) ## ----results="hide",eval = TRUE--------------------------- attach(teratology) ## ----eval = TRUE------------------------------------------ mLogit <- glm(cbind(D,L) ~ as.factor(Grp), family=binomial()) summary(mLogit) ## ----eval = TRUE------------------------------------------ mQuasi <- glm(cbind(D,L) ~ as.factor(Grp), family=quasibinomial(link="logit")) summary(mQuasi) ## ----eval = TRUE------------------------------------------ library(gee) ## ----results="hide",eval = TRUE--------------------------- detach(teratology) attach(teratology2) ## ----eval = TRUE------------------------------------------ mGee <- gee(y ~ as.factor(Grp), id=Rat, family=binomial) summary(mGee) ## ----eval = TRUE------------------------------------------ library(VGAM) ## ----results="hide",eval = TRUE--------------------------- detach(teratology2) attach(teratology) ## ----eval = TRUE------------------------------------------ N <- D + L ## ----eval = TRUE------------------------------------------ mBetaBin <- vglm(cbind(D,L) ~ as.factor(Grp), family=betabinomial, subset=N>1) summary(mBetaBin) ## ----results="hide",eval = TRUE--------------------------- detach(teratology) attach(teratology2) ## ----eval = TRUE------------------------------------------ mMixPql<- glmmPQL(y ~ as.factor(Grp), random=~1 | Rat, family=binomial) summary(mMixPql) ## ----eval = TRUE------------------------------------------ library(glmmML) ## ----eval = TRUE------------------------------------------ mGaussH <- glmmML(y ~ as.factor(Grp), cluster=Rat, method = "ghq", n.points = 14, boot = 0) summary(mGaussH) ## ----results="hide",eval = TRUE--------------------------- detach(teratology2) attach(teratology) ## ----eval = TRUE------------------------------------------ library(flexmix) ## ----results="hide",eval = TRUE--------------------------- detach(package:VGAM) library(stats4) ## ----eval = TRUE------------------------------------------ mDiscmix <-stepFlexmix(cbind(D,L) ~ 1, k = 2, nrep=5, model = FLXMRglmfix(family = "binomial",fixed =~as.factor(Grp))) summary(mDiscmix) parameters(mDiscmix)