Caesarian Birth Study
Data on infection from births by Caesarian section
data(caesar)
A data frame with 24 observations on the following 7 variables.
a factor with levels 1 2 3, the response
number of patients in group
a factor with levels not planned,
was the caesarian planned?
a factor with levels risk factors without,
was there risk factors?
a factor with levels antibiotics without
logistic response, 0=no infection
covariate pattern number
Infection from birth by Caesarian section. The response variable,
y, has levels 1=type I infection, 2=type II infection,
3=none infection. Where risk-factors (diabetes, overweight, others)
present? Where antibiotics used as prophylaxis? Aim is to
analyse effects on response by covariates.
Kjetil Halvorsen
Ludwig Fahrmeir, Gerhard Tutz (1994): Multivariate Statistical Modelling Based on Generalized Linear Models. Springer Series in Statistics. Springer Verlag. New-York Berlin Heidelberg
summary(caesar)
caesar.glm1 <- glm(yl ~ noplan+factor+antib, data=caesar, weight=w,
family=binomial(link="logit"))
caesar.glm2 <- glm(yl ~ noplan+factor+antib, data=caesar, weight=w,
family=binomial(link="probit"))
summary(caesar.glm1)
summary(caesar.glm2)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.