Journal
JOURNAL OF BIOPHARMACEUTICAL STATISTICS
Volume 32, Issue 3, Pages 441-449Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/10543406.2022.2080695
Keywords
Analyze as you randomize; Fisher's combination; minimization; multiple imputation; nonparametric combination of tests; randomization; re-randomization test
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This paper describes a randomization test for clinical trials using multiple imputation to handle missing data, illustrated with two post-traumatic stress disorder trials and Fisher's combining function applied to individual scores.
Randomization-based inference is a useful alternative to traditional population model-based methods. In trials with missing data, multiple imputation is often used. We describe how to construct a randomization test in clinical trials where multiple imputation is used for handling missing data. We illustrate the proposed methodology using Fisher's combining function applied to individual scores in two post-traumatic stress disorder trials.
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