… several binary outcomes from each cluster. Asymptotic methods are traditionally used for
confidence interval … sampling to further improve the performance of confidence intervals for ρ. …

… confidence interval based on the profile variance and reparameterization. Extensive simulation
studies show that the new confidence interval … better confidence interval in estimating K,. …

… form results in improved efficiency. The coverage of the confidence interval derived from
the … closer to the nominal level for the model including the covariate (see Fig. 2, Fig. 3, Fig. …

… They construct the first confidence interval by … exact confidence intervals that are more
computationally efficient. By exploiting recent advances in hypergeometric confidence intervals …

… model provided valid pooled effect measures and confidence intervals in this study.11
Another … In general, using Student t-distributed confidence intervals accounts better for the …

… -based confidence interval method, which we find to have better … confidence interval method
for independent binomial data and five existing confidence intervals for clustered binary data…

… 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 …

… However, reliable asymptotic confidence intervals for … confidence intervals for medical studies
with bilateral binary … model-based confidence intervals (ie, confidence intervals not being …

… These intervals tend to be more conservative when π = 0.30 or 0.50, but they are narrower
than those given by the same method when clusters are divided into pairs (ie mean width 0.08…

… considered sufficient to let us measure binary outcomes to a confidence interval (CI) width of
0.08 … suggest that the analysis and reporting of binary endpoints in RCTs needs to improve. …