Mixed-effects Models for Repeated Measures in Longitudinal Data Analysis: An Introduction to Methodology, Theory, and Applications
Author:
Affiliation:
1. Department of Clinical Trial and Clinical Epidemiology, Faculty of Medicine, University of Tsukuba
2. Translational Medical Center, National Center of Neurology and Psychiatry
Publisher
Japanese Society of Applied Statistics
Subject
General Medicine
Link
https://www.jstage.jst.go.jp/article/jappstat/46/2/46_53/_pdf
Reference41 articles.
1. Barnes, S.A., Mallinckrodt, C.H., Lindborg, S.R. and Carter, M.K. (2008): The impact of missing data and how it is handled on the rate of false-positive results in drug development. Pharmaceutical Statistics 7, 215-225.
2. Committee for Medical Products for Human Use (2010): Guideline on Missing Data in Confirmatory Clinical Trials. European Medicines Evaluation Agency, London.
3. Demidenko, E. (2004): Mixed Models: Theory and Applications. John Wiley & Sons.
4. DeSouza, C.M., Legedza, A.T. and Sankoh, A.J. (2009): An overview of practical approaches for handling missing data in clinical trials. Journal of Biopharmaceutical Statistics 19, 1055-1073.
5. Fay, M.P. and Graubard, B.I. (2001): Small-sample adjustments for Wald-type tests using sandwich estimators. Biometrics 57, 1198-1206.
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