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, 645650.
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(survival5)){ faketime <- rep(42,nrow(infert)) model3 <- coxph(Surv(faketime,case)~spontaneous+induced+strata(stratum), data=infert,method="exact") summary(model3) detach()# survival5 (conflicts) }