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 …

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

While the commonly used log-rank test for survival times between 2 groups enjoys many
desirable properties, sometimes the log-rank test and its related linear rank tests perform …

When conducting statistical inference to compare two independent proportions in either a
randomized clinical trial or an observational study, researchers commonly use relative risk to …

Background Incomplete data often arise in various clinical trials such as crossover trials,
equivalence trials, and pre and post-test comparative studies. Various methods have been …

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 …

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

An experiment to assess the efficacy of a particular treatment or process often produces
dichotomous responses, either favourable or unfavourable. When we administer the …

We have presented a new likelihood‐based approach for constructing confidence intervals
of effect size that are applicable to small samples. We also conduct a simulation study to …

In this paper, we propose two new methods for computing confidence intervals for the
difference of two independent binomial proportions in small sample cases. Several test …