In cohort studies, the risk ratio (RR) is one of the most commonly used epi
demiologic indices to quantify the effect of a suspected risk factor on the
probability of developing a disease. When we employ cluster sampling to co
llect data, an interval estimator that does not account for the intraclass
correlation between subjects within clusters is likely inappropriate. In ap
plication of the beta-binomial model to account for the intraclass correlat
ion, we develop four asymptotic interval estimators of the RR, which are di
rect extensions of some recently developed estimators for independent binom
ial sampling. We then use Monte Carlo simulation to evaluate the finite-sam
ple performance of these four interval estimators in a variety of situation
s. We find that the estimator using the logarithmic transformation generall
y performs well and is preferable to the other three estimators in most of
the situations considered here. Finally, we include an example from a study
of an educational intervention with emphasis on behaviour change to illust
rate the use of the estimators developed in this paper. Copyright (C) 2000
John Wiley & Sons, Ltd.