Literature DB >> 22162151

Sample size calculations with multiplicity adjustment for longitudinal clinical trials with missing data.

Kaifeng Lu1.   

Abstract

Missing data are ubiquitous in longitudinal clinical trials, and the impact on power has been extensively assessed in the literature. Multiple doses of the investigational product and multiple efficacy endpoints are often studied in randomized clinical trials and multiplicity adjustment needs to be considered in the sample size calculations. In this paper, I show how to perform sample size calculations with multiplicity adjustment for longitudinal clinical trials with missing data by converting longitudinal data with missing data to cross-sectional data without missing data. The proposed approach can drastically simplify the simulation work and facilitate the evaluation of power for various scenarios.
Copyright © 2011 John Wiley & Sons, Ltd.

Mesh:

Year:  2011        PMID: 22162151     DOI: 10.1002/sim.4415

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  Sample Size Calculations for Time-Averaged Difference of Longitudinal Binary Outcomes.

Authors:  Ying Lou; Jing Cao; Song Zhang; Chul Ahn
Journal:  Commun Stat Theory Methods       Date:  2016-02-18       Impact factor: 0.893

2.  Power and Sample Size for Fixed-Effects Inference in Reversible Linear Mixed Models.

Authors:  Yueh-Yun Chi; Deborah H Glueck; Keith E Muller
Journal:  Am Stat       Date:  2018-06-04       Impact factor: 8.710

3.  A Randomized, Double-Blind, Placebo-Controlled Trial of Vilazodone in Children and Adolescents with Major Depressive Disorder with Twenty-Six-Week Open-Label Follow-Up.

Authors:  Robert L Findling; Emily McCusker; Jeffrey R Strawn
Journal:  J Child Adolesc Psychopharmacol       Date:  2020-05-27       Impact factor: 2.576

  3 in total

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