JSM 2005 - Toronto

Abstract #302660

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 241
Type: Invited
Date/Time: Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Consulting
Abstract - #302660
Title: Accounting for Alignment, Uncertainty, and Bias in Choosing a Sample Size
Author(s): Michael R. Jiroutek*+ and Keith E. Muller
Companies: Salix Pharmaceuticals, Inc. and University of North Carolina, Chapel Hill
Address: 1700 Perimeter Park Drive, Morrisville, NC, 27560,
Keywords: power ; width ; rejection ; validity ; truncation
Abstract:

Historically, the sample size chosen for a study aimed at estimating a confidence interval (CI) controlled only the probability of width (the CI is as narrow as desired). In contrast, a new criterion controls the probability of width and rejection (of the null hypothesis), given validity (the interval contains the true parameter). The new approach better aligns the sample size rule with common scientific goals. We restrict attention to scalar parameters in linear models with Gaussian errors. The variance used to choose the sample size for a target study is often an estimate from a screening study. We describe how to compute an exact CI for a value of the new criterion when based on such an estimate. Such CIs can be distressingly wide when based on a small screening study, even if the target study sample size is large. A target study performed only due to a significant (or nonsignificant) screening study causes truncation of the error variance density. In turn, the sample size may be optimistically (or pessimistically) biased. Exact CIs for the new probability criterion allow eliminating the bias. Many familiar criteria are special cases of the new conditional probability.

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Revised March 2005