首页|Power and sample size for fixed-effects inference in reversible linear mixed models
Power and sample size for fixed-effects inference in reversible linear mixed models
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Though the general linear mixed model for data analysis is highly popular, the power and sample size methods are applicable only to special cases and in other situations, only rough approximations are used. While no software packages are available for this, accurate methods and software for power and sample size are available for linear multivariate models. Many applications in health sciences use special cases corresponding to multivariate models. It is necessary to know the conditions under which a mixed model can use power and sample size methods for a multivariate linear model. There are types of general linear mixed models including longitudinal and cluster designs that can use power and sample size methods and existing software. Though all multivariate models can be stated as mixed models, the converse is not true. Any mixed model can be converted into a multivariate model and vice versa meaning the process is reversible. So for reversible models, the power and sample size can be exactly computed. The objective of this study is to identify if reversible models are practical. The test statistic in many mixed models corresponds to that of multivariate test statistic for which power and sample size can be derived. The method is to use Wald test of fixed effects in the general linear model which has power equivalent to that of a general linear hypothesis test in the general multivariate model, and the power-equivalent hypothesis is reversible.
Yueh-Yun Chi、Deborah H.Clueck、Keith E. Muller
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Department of Biostatistics, University of Florida, Gainesville, FL
Department of Paediatrics, University of Colorado Denver, Denver, CO
Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL
NSTL
