infert {base} | R Documentation |
This is a matched case-control study dating from before the availability of conditional logistic regression.
data(infert)
1. | Education | 0 = 0-5 years |
1 = 6-11 years | ||
2 = 12+ years | ||
2. | age | age in years of case |
3. | parity | count |
4. | number of prior | 0 = 0 |
induced abortions | 1 = 1 | |
2 = 2 or more | ||
5. | case status | 1 = case |
0 = control | ||
6. | number of prior | 0 = 0 |
spontaneous abortions | 1 = 1 | |
2 = 2 or more | ||
7. | matched set number | 1-83 |
8. | stratum number | 1-63 |
One case with two prior spontaneous abortions and two prior induced abortions is omitted.
Trichopoulos et al. (1976) Br. J. of Obst. and Gynaec. 83, 645–650.
data(infert)
model1 <- glm(case ~ spontaneous+induced, data=infert,family=binomial())
summary(model1)
## adjusted for other potential confounders:
summary(model2 <- glm(case ~ age+parity+education+spontaneous+induced,
data=infert,family=binomial()))
## Really should be analysed by conditional logistic regression
## which is equivalent to a Cox model :
if(require(survival)){
oT <- T; oF <- F; T <- TRUE; F <- FALSE # survival fails otherwise
faketime <- rep(42,nrow(infert))
model3 <- coxph(Surv(faketime,case)~spontaneous+induced+strata(stratum),
data=infert,method="exact")
summary(model3)
detach()# survival (conflicts)
T <- oT; F <- oF
}