Literature DB >> 19321221

A SAS macro for a clustered permutation test.

Margaret R Stedman1, David R Gagnon, Robert A Lew, Daniel H Solomon, Elena Losina, M Alan Brookhart.   

Abstract

The clustered permutation test is a nonparametric method of significance testing for correlated data. It is often used in cluster randomized trials where groups of patients rather than individuals are randomized to either a treatment or control intervention. We describe a flexible and efficient SAS macro that implements the 2-sample clustered permutation test. We discuss the theory and applications behind this test as well as details of the SAS code.

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Year:  2009        PMID： 19321221      PMCID： PMC2674116          DOI： 10.1016/j.cmpb.2009.02.005

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN： 0169-2607            Impact factor:   5.428


  7 in total

1.  A comparison of permutation and mixed-model regression methods for the analysis of simulated data in the context of a group-randomized trial.

Authors:  David M Murray; Peter J Hannan; Sherri P Pals; Richard G McCowen; William L Baker; Jonathan L Blitstein
Journal:  Stat Med       Date:  2006-02-15       Impact factor: 2.373

2.  Development of an efficient SAS macro to perform permutation tests for two independent samples.

Authors:  G K Balasubramani; Stephen R Wisniewski; Hongwei Zhang; Heather F Eng
Journal:  Comput Methods Programs Biomed       Date:  2005-08       Impact factor: 5.428

3.  An evaluation of statistical approaches for analyzing physician-randomized quality improvement interventions.

Authors:  Margaret R Stedman; David R Gagnon; Robert A Lew; Daniel H Solomon; M Alan Brookhart
Journal:  Contemp Clin Trials       Date:  2008-04-23       Impact factor: 2.226

Review 4.  On design considerations and randomization-based inference for community intervention trials.

Authors:  M H Gail; S D Mark; R J Carroll; S B Green; D Pee
Journal:  Stat Med       Date:  1996-06-15       Impact factor: 2.373

5.  Statistical considerations in the design and analysis of community intervention trials.

Authors:  A Donner; N Klar
Journal:  J Clin Epidemiol       Date:  1996-04       Impact factor: 6.437

6.  Pros and cons of permutation tests in clinical trials.

Authors:  V W Berger
Journal:  Stat Med       Date:  2000-05-30       Impact factor: 2.373

7.  Improving care of patients at-risk for osteoporosis: a randomized controlled trial.

Authors:  Daniel H Solomon; Jennifer M Polinski; Margaret Stedman; Colleen Truppo; Laura Breiner; Catherine Egan; Saira Jan; Minal Patel; Thomas W Weiss; Ya-ting Chen; M Alan Brookhart
Journal:  J Gen Intern Med       Date:  2007-03       Impact factor: 5.128
  7 in total
  2 in total

1.  A comparison of statistical approaches for physician-randomized trials with survival outcomes.

Authors:  Margaret R Stedman; Robert A Lew; Elena Losina; David R Gagnon; Daniel H Solomon; M Alan Brookhart
Journal:  Contemp Clin Trials       Date:  2011-09-06       Impact factor: 2.226

2.  Comparison of CaOH with MTA for direct pulp capping: a PBRN randomized clinical trial.

Authors:  T J Hilton; J L Ferracane; L Mancl
Journal:  J Dent Res       Date:  2013-05-20       Impact factor: 6.116
  2 in total

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