caesar {Fahrmeir}

Caesarian Birth Study

Description

Data on infection from births by Caesarian section

Usage

data(caesar)

Format

A data frame with 24 observations on the following 7 variables.

y

a factor with levels 1 2 3, the response

w

number of patients in group

noplan

a factor with levels not planned, was the caesarian planned?

factor

a factor with levels risk factors without, was there risk factors?

antib

a factor with levels antibiotics without

yl

logistic response, 0=no infection

patco

covariate pattern number

Details

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.

Author(s)

Kjetil Halvorsen

Source

Ludwig Fahrmeir, Gerhard Tutz (1994): Multivariate Statistical Modelling Based on Generalized Linear Models. Springer Series in Statistics. Springer Verlag. New-York Berlin Heidelberg

Examples

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)