Clustered binary data are commonly encountered in many medical research studies with
several binary outcomes from each cluster. Asymptotic methods are traditionally used for …

Estimating the precision of a single proportion via a 100 (1− α)% confidence interval in the
presence of clustered data is an important statistical problem. It is necessary to account for …

Interval estimation of the proportion parameter in the analysis of binary outcome data arising
in cluster studies is often an important problem in many biomedical applications. In this …

We used simulation to compare accuracy of estimation and confidence interval coverage of
several methods for analysing binary outcomes from cluster randomized trials. The following …

Although there are several available test statistics to assess the difference of marginal
probabilities in clustered matched‐pair binary data, associated confidence intervals (CIs) …

The intraclass correlation in binary outcome data sampled from clusters is an important and
versatile measure in many biological and biomedical investigations. Properties of the …

In cohort studies, the risk ratio (RR) is one of the most commonly used epidemiologic indices
to quantify the effect of a suspected risk factor on the probability of developing a disease …

We propose two measures of performance for a confidence interval for a binomial proportion
p: the root mean squared error and the mean absolute deviation. We also devise a …

Paired dichotomous data may arise in clinical trials such as pre‐/post‐test comparison
studies and equivalence trials. Reporting parameter estimates (eg odds ratio, rate difference …

A cluster randomization trial is one in which clusters of individuals are randomly allocated to
different intervention arms. This design has become the standard for the evaluation of health …