Literature DB >> 10407230

Estimating the sample size for a t-test using an internal pilot.

J S Denne1, C Jennison.   

Abstract

If the sample size for a t-test is calculated on the basis of a prior estimate of the variance then the power of the test at the treatment difference of interest is not robust to misspecification of the variance. We propose a t-test for a two-treatment comparison based on Stein's two-stage test which involves the use of an internal pilot to estimate variance and thus the final sample size required. We evaluate our procedure's performance and show that it controls the type I and II error rates more closely than existing methods for the same problem. We also propose a rule for choosing the size of the internal pilot, and show that this is reasonable in terms of the efficiency of the procedure. Copyright 1999 John Wiley & Sons, Ltd.

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Year:  1999        PMID: 10407230     DOI: 10.1002/(sici)1097-0258(19990715)18:13<1575::aid-sim153>3.0.co;2-z

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


  9 in total

1.  Combining an Internal Pilot with an Interim Analysis for Single Degree of Freedom Tests.

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3.  GLUMIP 2.0: SAS/IML Software for Planning Internal Pilots.

Authors:  John A Kairalla; Christopher S Coffey; Keith E Muller
Journal:  J Stat Softw       Date:  2008-11-13       Impact factor: 6.440

4.  Internal pilot design for balanced repeated measures.

Authors:  Xinrui Zhang; Keith E Muller; Maureen M Goodenow; Yueh-Yun Chi
Journal:  Stat Med       Date:  2017-11-21       Impact factor: 2.373

5.  Options and Considerations for Adaptive Laboratory Experiments.

Authors:  Lai Wei; David Jarjoura
Journal:  Stat Biosci       Date:  2014-11-25

6.  An internal pilot design for prospective cancer screening trials with unknown disease prevalence.

Authors:  John T Brinton; Brandy M Ringham; Deborah H Glueck
Journal:  Trials       Date:  2015-10-13       Impact factor: 2.279

7.  Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable.

Authors:  Amy L Whitehead; Steven A Julious; Cindy L Cooper; Michael J Campbell
Journal:  Stat Methods Med Res       Date:  2015-06-19       Impact factor: 3.021

8.  Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

Authors:  Cornelia U Kunz; Nigel Stallard; Nicholas Parsons; Susan Todd; Tim Friede
Journal:  Biom J       Date:  2016-11-25       Impact factor: 2.207

9.  Estimation after blinded sample size reassessment.

Authors:  Martin Posch; Florian Klinglmueller; Franz König; Frank Miller
Journal:  Stat Methods Med Res       Date:  2016-10-02       Impact factor: 3.021

  9 in total

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