A comparative appraisal of two equivalence tests for multiple standardized effects. Issue 126 (April 2016)

• Record Type: Journal Article
• Authors: Shieh, Gwowen
• Is Part Of: Computer methods and programs in biomedicine. Issue 126(2016)
• Page Start: 110
• Page End: 117
• Publication Date: 2016-04
• Subjects: Effect size -- Power -- Sample size -- Standardized mean difference; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2015.12.004
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: This article explicates and evaluates the features of the ANOVA F test and the studentized range test for determining the equivalence of multiple standardized effects. The primary emphasis is to reveal the underlying properties of the two methods with regard to power behavior and sample size requirement across a variety of design configurations. To enhance the practical usefulness, complete sets of SAS and R computer algorithms for calculating the critical values, p -values, power levels, and sample sizes are also developed. Abstract: Equivalence testing is recommended as a better alternative to the traditional difference-based methods for demonstrating the comparability of two or more treatment effects. Although equivalent tests of two groups are widely discussed, the natural extensions for assessing equivalence between several groups have not been well examined. This article provides a detailed and schematic comparison of the ANOVA F and the studentized range tests for evaluating the comparability of several standardized effects. Power and sample size appraisals of the two grossly distinct approaches are conducted in terms of a constraint on the range of the standardized means when the standard deviation of the standardized means is fixed. Although neither method is uniformly more powerful, the studentized range test has a clear advantage in sample size requirements necessary to achieve a given power when the underlying effect configurations are close to the priori minimum difference for determining equivalence. For actual application of equivalence tests and advance planning of equivalence studies, both SAS and R computer codes are available as supplementary files to implement the calculations of critical values, p -values, power levels, and sample sizes.