Literature DB >> 19053162

Effects of correlation and missing data on sample size estimation in longitudinal clinical trials.

Song Zhang1, Chul Ahn.   

Abstract

In longitudinal clinical trials, a common objective is to compare the rates of changes in an outcome variable between two treatment groups. Generalized estimating equation (GEE) has been widely used to examine if the rates of changes are significantly different between treatment groups due to its robustness to misspecification of the true correlation structure and randomly missing data. The sample size formula for repeated outcomes is based on the assumption of missing completely at random and a large sample approximation. A simulation study is conducted to investigate the performance of GEE sample size formula with small sample sizes, damped exponential family of correlation structure and non-ignorable missing data. (c) 2008 John Wiley & Sons, Ltd.

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Year:  2010        PMID: 19053162      PMCID: PMC2885769          DOI: 10.1002/pst.359

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  4 in total

1.  Sample size estimation for GEE method for comparing slopes in repeated measurements data.

Authors:  Sin-Ho Jung; Chul Ahn
Journal:  Stat Med       Date:  2003-04-30       Impact factor: 2.373

2.  A parametric family of correlation structures for the analysis of longitudinal data.

Authors:  A Muñoz; V Carey; J P Schouten; M Segal; B Rosner
Journal:  Biometrics       Date:  1992-09       Impact factor: 2.571

3.  Application of GEE procedures for sample size calculations in repeated measures experiments.

Authors:  J Rochon
Journal:  Stat Med       Date:  1998-07-30       Impact factor: 2.373

4.  Sample size calculations for studies with correlated observations.

Authors:  G Liu; K Y Liang
Journal:  Biometrics       Date:  1997-09       Impact factor: 2.571

  4 in total
  3 in total

1.  Adding Subjects or Adding Measurements in Repeated Measurement Studies Under Financial Constraints.

Authors:  Song Zhang; Chul Ahn
Journal:  Stat Biopharm Res       Date:  2011-02-01       Impact factor: 1.452

2.  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

3.  How many measurements for time-averaged differences in repeated measurement studies?

Authors:  Song Zhang; Chul Ahn
Journal:  Contemp Clin Trials       Date:  2011-01-15       Impact factor: 2.226

  3 in total

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