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Improved Small Sample Inference Methods for a Mixed-Effects Model for Repeated Measures Approach in Incomplete Longitudinal Data Analysis

1
Department of Biostatistics, Janssen Pharmaceutical K. K., 5-2 Nishi-kanda 3-chome, Chiyoda-ku, Tokyo 101-0065, Japan
2
Department of Statistical Science, School of Multidisciplinary Sciences, The Graduate University for Advanced Studies, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan
3
Department of Data Science, The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan
4
Department of Biostatistics, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan
*
Author to whom correspondence should be addressed.
Stats 2019, 2(2), 174-188; https://doi.org/10.3390/stats2020013
Received: 16 January 2019 / Revised: 15 March 2019 / Accepted: 23 March 2019 / Published: 28 March 2019
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Abstract

The mixed-effects model for repeated measures (MMRM) approach has been widely applied for longitudinal clinical trials. Many of the standard inference methods of MMRM could possibly lead to the inflation of type I error rates for the tests of treatment effect, when the longitudinal dataset is small and involves missing measurements. We propose two improved inference methods for the MMRM analyses, (1) the Bartlett correction with the adjustment term approximated by bootstrap, and (2) the Monte Carlo test using an estimated null distribution by bootstrap. These methods can be implemented regardless of model complexity and missing patterns via a unified computational framework. Through simulation studies, the proposed methods maintain the type I error rate properly, even for small and incomplete longitudinal clinical trial settings. Applications to a postnatal depression clinical trial are also presented. View Full-Text
Keywords: Bartlett adjustment; MMRM; missing data; longitudinal data analysis; resampling Bartlett adjustment; MMRM; missing data; longitudinal data analysis; resampling
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Ukyo, Y.; Noma, H.; Maruo, K.; Gosho, M. Improved Small Sample Inference Methods for a Mixed-Effects Model for Repeated Measures Approach in Incomplete Longitudinal Data Analysis. Stats 2019, 2, 174-188.

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