Literature DB >> 7906957

Size and power of two-sample tests of repeated measures data.

J D Dawson1, S W Lagakos.   

Abstract

One method of using repeated measures data to compare treatment groups in a clinical trial is to summarize each subject's outcomes with a single summary statistic, and then perform a distribution-free comparison based on the resulting statistics. We examine extensions of this approach and conditions under which they retain proper size in the presence of missing data. The asymptotic relative efficiencies of several summary statistic tests are calculated to show which perform best in a variety of situations. The techniques are illustrated using data from an AIDS clinical trial.

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Year:  1993        PMID: 7906957

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  9 in total

1.  Effectiveness of remune.

Authors:  D Glidden; S Kim; S Lagakos
Journal:  Clin Diagn Lab Immunol       Date:  2001-03

2.  Simulation study of power and sample size for repeated measures with multinomial outcomes: an application to sound direction identification experiments (SDIE).

Authors:  Dingfeng Jiang; Jacob J Oleson
Journal:  Stat Med       Date:  2011-07-12       Impact factor: 2.373

3.  Serving street-dwelling individuals with psychiatric disabilities: outcomes of a psychiatric rehabilitation clinical trial.

Authors:  D L Shern; S Tsemberis; W Anthony; A M Lovell; L Richmond; C J Felton; J Winarski; M Cohen
Journal:  Am J Public Health       Date:  2000-12       Impact factor: 9.308

4.  A comparison of power analysis methods for evaluating effects of a predictor on slopes in longitudinal designs with missing data.

Authors:  Cuiling Wang; Charles B Hall; Mimi Kim
Journal:  Stat Methods Med Res       Date:  2012-02-21       Impact factor: 3.021

5.  Tiapride pre-treatment in acute exposure to paraoxon: comparison of effects of administration at different points-in-time in rats.

Authors:  G A Petroianu; M Y Hasan; S M Nurulain; K Arafat; M Shafiullah; R Sheen
Journal:  Mol Cell Biochem       Date:  2006-02-15       Impact factor: 3.396

6.  The impact of loss to follow-up on hypothesis tests of the treatment effect for several statistical methods in substance abuse clinical trials.

Authors:  Sarra L Hedden; Robert F Woolson; Rickey E Carter; Yuko Palesch; Himanshu P Upadhyaya; Robert J Malcolm
Journal:  J Subst Abuse Treat       Date:  2008-11-13

7.  Assessing atrophy measurement techniques in dementia: Results from the MIRIAD atrophy challenge.

Authors:  David M Cash; Chris Frost; Leonardo O Iheme; Devrim Ünay; Melek Kandemir; Jurgen Fripp; Olivier Salvado; Pierrick Bourgeat; Martin Reuter; Bruce Fischl; Marco Lorenzi; Giovanni B Frisoni; Xavier Pennec; Ronald K Pierson; Jeffrey L Gunter; Matthew L Senjem; Clifford R Jack; Nicolas Guizard; Vladimir S Fonov; D Louis Collins; Marc Modat; M Jorge Cardoso; Kelvin K Leung; Hongzhi Wang; Sandhitsu R Das; Paul A Yushkevich; Ian B Malone; Nick C Fox; Jonathan M Schott; Sebastien Ourselin
Journal:  Neuroimage       Date:  2015-08-11       Impact factor: 6.556

8.  Two-period linear mixed effects models to analyze clinical trials with run-in data when the primary outcome is continuous: Applications to Alzheimer's disease.

Authors:  Guoqiao Wang; Andrew J Aschenbrenner; Yan Li; Eric McDade; Lei Liu; Tammie L S Benzinger; Randall J Bateman; John C Morris; Jason J Hassenstab; Chengjie Xiong
Journal:  Alzheimers Dement (N Y)       Date:  2019-09-05

9.  A comparison of missing data methods for hypothesis tests of the treatment effect in substance abuse clinical trials: a Monte-Carlo simulation study.

Authors:  Sarra L Hedden; Robert F Woolson; Robert J Malcolm
Journal:  Subst Abuse Treat Prev Policy       Date:  2008-06-03
  9 in total

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