dat<-read.csv("http://peach.l.chiba-u.ac.jp/course_folder/logisticReg01.txt ")
plot(dat$study, dat$pass, pch=20,ylab="Passed or not",xlab="Hours studied",cex=2,cex.lab=1.5,yaxt='n')
dat.lr <- glm(pass~study,family=binomial, data=dat)
summary(dat.lr)
coef = coefficients(dat.glm)
pred.pass.p = 1/(1+exp(-(coef[1]+coef[2]*0:30)))

##
pred.pass.p = 1/(1+exp(-(coef[1]+coef[2]*c(10:15))))
odds=pred.pass.p/(1-pred.pass.p)
exp(coef[2])

dat<-read.csv("http://www.matsuka.info/data_folder/datWA01.txt")
dat.lr<-glm(gender~shoesize,family=binomial,data=dat)
anova(dat.lr, test ="Chisq")
dat.lr0<-glm(gender~1,family="binomial",data=dat)
dat.lrS<-glm(gender~shoesize,family=binomial,data=dat)
dat.lrh<-glm(gender~h,family="binomial",data=dat)


M=matrix(c(52,48,8,42),nrow=2)
rownames(M)<-c("present", "absent")
colnames(M)<-c("smoker",'non-smoker')
dat<-as.data.frame((as.table(M)))
colnames(dat)<-c("cancer","smoking","freq")
dat=dat[rep(1:nrow(dat),dat$freq),1:2]
rownames(dat)<-c()

dat.glm<-glm(cancer~smoking,family=binomial,data=dat)
dat<-read.csv("http://www.matsuka.info/data_folder/cda7-16.csv")
dat.glm<-glm(survival~age, family=binomial,data=dat)
dat.glm2<-glm(survival~Ncigarettes,family=binomial,data=dat)
dat.glm3<-glm(survival~NdaysGESTATION,family=binomial,data=dat)
dat.glmAllAdd=glm(survival~age+Ncigarettes+NdaysGESTATION,family=binomial,data=dat)
dat.glmAllMult=glm(survival~age*Ncigarettes*NdaysGESTATION,family=binomial,data=dat)
library(MASS)


dat<-read.csv("http://peach.l.chiba-u.ac.jp/course_folder/poissonReg01.txt ")
dat.pr<-glm(eye.count~attr,family = "poisson",data=dat)