Statistical methodologies to pool across multiple intervention studies

Statistical methodologies to pool across multiple intervention studies.

Combining and analyzing data from heterogeneous randomized controlled trials of complex multiple-component intervention studies, or discussing them in a systematic review, is not straightforward. The present article describes certain issues to be considered when combining data across studies, based on discussions in an NIH-sponsored workshop on pooling issues across studies in consortia (see Be...

Effective Methodologies for Statistical Inference on Microarray Studies

Guide to the use of statistical methods in clinical studies

This article has no abstract.

Statistical Approaches to Modeling Multiple Outcomes In Psychiatric Studies.

Increasingly, multiple outcomes are collected in order to characterize treatment effectiveness or to evaluate risk factors. These outcomes tend to be correlated because they are measuring related quantities in the same individuals. While the analysis of outcomes measured in the same scale (commensurate outcomes) can be undertaken with standard statistical methods, outcomes measured in different...

Statistical power in randomized intervention studies with noncompliance.

This study examined various factors that affect statistical power in randomized intervention studies with noncompliance. On the basis of Monte Carlo simulations, this study demonstrates how statistical power changes depending on compliance rate, study design, outcome distributions, and covariate information. It also examines how these factors influence power in different methods of estimating i...