The literature of multiple comparison methods addresses the problem of ranking treatments groups from best to worst. However, there is no clear indication of how to deal with the information from multiple comparisons, particularly in case of blocking (or stratification) or in case of multivariate response variables. In the present paper we take three methods into consideration to produce a performance ranking of C treatments under study. By means of a simulation study, it is possible to calculate the percentage of correct classifications of the compared methods and to study their performances. The proposed study also allows us to determine the minimum sample size useful for detecting performance differences among treatments.
Sample Size Determination for Multivariate Performance Analysis with Complex Design
CORAIN, LIVIO;SALMASO, LUIGI
2010
Abstract
The literature of multiple comparison methods addresses the problem of ranking treatments groups from best to worst. However, there is no clear indication of how to deal with the information from multiple comparisons, particularly in case of blocking (or stratification) or in case of multivariate response variables. In the present paper we take three methods into consideration to produce a performance ranking of C treatments under study. By means of a simulation study, it is possible to calculate the percentage of correct classifications of the compared methods and to study their performances. The proposed study also allows us to determine the minimum sample size useful for detecting performance differences among treatments.Pubblicazioni consigliate
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