Literature DB >> 15344187

Power analyses for longitudinal trials and other clustered designs.

X M Tu1, J Kowalski, J Zhang, K G Lynch, P Crits-Christoph.   

Abstract

Existing methods for power and sample size estimation for longitudinal and other clustered study designs have limited applications. In this paper, we review and extend existing approaches to improve these limitations. In particular, we focus on power analysis for the two most popular approaches for clustered data analysis, the generalized estimating equations and the linear mixed-effects models. By basing the derivation of the power function on the asymptotic distribution of the model estimates, the proposed approach provides estimates of power that are consistent with the methods of inference for data analysis. The proposed methodology is illustrated with numerous examples that are motivated by real study designs. Copyright 2004 John Wiley & Sons, Ltd.

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Year:  2004        PMID: 15344187     DOI: 10.1002/sim.1869

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


  16 in total

1.  Variation in OPRM1 and risk of suicidal behavior in drug-dependent individuals.

Authors:  Albert J Arias; Grace Chan; Joel Gelernter; Lindsay Farrer; Henry R Kranzler
Journal:  Am J Addict       Date:  2011-12-15

2.  A pragmatic trial of a group intervention in senior housing communities to increase resilience.

Authors:  Emily B H Treichler; Danielle Glorioso; Ellen E Lee; Tsung-Chin Wu; Xin M Tu; Rebecca Daly; Catherine O'Brien; Jennifer L Smith; Dilip V Jeste
Journal:  Int Psychogeriatr       Date:  2020-02-05       Impact factor: 3.878

3.  Comparative Effectiveness of Cognitive Therapy and Dynamic Psychotherapy for Major Depressive Disorder in a Community Mental Health Setting: A Randomized Clinical Noninferiority Trial.

Authors:  Mary Beth Connolly Gibbons; Robert Gallop; Donald Thompson; Debra Luther; Katherine Crits-Christoph; Julie Jacobs; Seohyun Yin; Paul Crits-Christoph
Journal:  JAMA Psychiatry       Date:  2016-09-01       Impact factor: 21.596

4.  Power and sample size calculations for longitudinal studies estimating a main effect of a time-varying exposure.

Authors:  Xavier Basagaña; Donna Spiegelman
Journal:  Stat Methods Med Res       Date:  2010-06-14       Impact factor: 3.021

5.  Optimal combination of number of participants and number of repeated measurements in longitudinal studies with time-varying exposure.

Authors:  Jose Barrera-Gómez; Donna Spiegelman; Xavier Basagaña
Journal:  Stat Med       Date:  2013-06-05       Impact factor: 2.373

6.  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

7.  Using interactive Internet technology to promote physical activity in Latinas: Rationale, design, and baseline findings of Pasos Hacia La Salud.

Authors:  Bess H Marcus; Sheri J Hartman; Dori Pekmezi; Shira I Dunsiger; Sarah E Linke; Becky Marquez; Kim M Gans; Beth C Bock; Britta A Larsen; Carlos Rojas
Journal:  Contemp Clin Trials       Date:  2015-08-05       Impact factor: 2.226

8.  Power and sample size calculations for longitudinal studies comparing rates of change with a time-varying exposure.

Authors:  X Basagaña; D Spiegelman
Journal:  Stat Med       Date:  2010-01-30       Impact factor: 2.373

9.  Sample size calculations for micro-randomized trials in mHealth.

Authors:  Peng Liao; Predrag Klasnja; Ambuj Tewari; Susan A Murphy
Journal:  Stat Med       Date:  2015-12-28       Impact factor: 2.373

10.  A power approximation for the Kenward and Roger Wald test in the linear mixed model.

Authors:  Sarah M Kreidler; Brandy M Ringham; Keith E Muller; Deborah H Glueck
Journal:  PLoS One       Date:  2021-07-21       Impact factor: 3.240

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