Efficient design and sample size calculation for trials with clustered data
نویسندگان
چکیده
منابع مشابه
Sample size determination for clustered count data.
We consider the problem of sample size determination for count data. Such data arise naturally in the context of multicenter (or cluster) randomized clinical trials, where patients are nested within research centers. We consider cluster-specific and population-averaged estimators (maximum likelihood based on generalized mixed-effect regression and generalized estimating equations, respectively)...
متن کاملSimple sample size calculation for cluster-randomized trials.
BACKGROUND Cluster-randomized trials, in which health interventions are allocated randomly to intact clusters or communities rather than to individual subjects, are increasingly being used to evaluate disease control strategies both in industrialized and in developing countries. Sample size computations for such trials need to take into account between-cluster variation, but field epidemiologis...
متن کاملEfficient Bayesian Sample Size Calculation for Designing a Clinical Trial with Multi-Cluster Outcome Data
Health care utilization and outcome studies call for hierarchical approaches. The objectives were to predict major complications following percutaneous coronary interventions by health providers, and to compare Bayesian and non-Bayesian sample size calculation methods. The hierarchical data structure consisted of: (1) Strata: PGY4, PGY7, and physician assistant as providers with varied experien...
متن کاملReporting of sample size calculation in randomised controlled trials: review
OBJECTIVES To assess quality of reporting of sample size calculation, ascertain accuracy of calculations, and determine the relevance of assumptions made when calculating sample size in randomised controlled trials. DESIGN Review. DATA SOURCES We searched MEDLINE for all primary reports of two arm parallel group randomised controlled trials of superiority with a single primary outcome publi...
متن کاملSample Size Calculation for Comparing Time-to-event Data
In clinical research, the occurrence of certain events (e.g., adverse events, disease progression, relapse, or death) is often of particular interest to the investigators, especially in the area of cancer trials. In most situations, these events are undesirable and unpreventable. In practice, it would be beneficial to patients if the test treatment could delay the occurrence of such events. As ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical Methods in Medical Research
سال: 2015
ISSN: 0962-2802,1477-0334
DOI: 10.1177/0962280215608718