Statistics in medicine
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Statistics in medicine · Apr 2000
Review Comparative StudyStrategies for comparing treatments on a binary response with multi-centre data.
This paper surveys methods for comparing treatments on a binary response when observations occur for several strata. A common application is multi-centre clinical trials, in which the strata refer to a sample of centres or sites of some type. Questions of interest include how one should summarize the difference between the treatments, how one should make inferential comparisons, how one should investigate whether treatment-by-centre interaction exists, how one should describe effects when interaction exists, whether one should treat centres and centre-specific treatment effects as fixed or random, and whether centres that have either 0 successes or 0 failures should contribute to the analysis. This article discusses these matters in the context of various strategies for analysing such data, in particular focusing on special problems presented by sparse data.
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Analyses of dose response studies should separate the question of the existence of a dose response relationship from questions of functional form and finding the optimal dose. A well-chosen contrast among the estimated effects of the studied doses can make a powerful test for detecting the existence of a dose response relationship. A contrast-based test attains its greatest power when the pattern of the coefficients has the same shape as the true dose response relationship. ⋯ Thus, a primary test based on a single contrast is often risky. Two (or more) appropriately chosen contrasts can assure sufficient power to justify the cost of a multiplicity adjustment. An example shows the success of a two-contrast procedure in detecting dose response, which had frustrated several standard procedures.