Internal pilot design for balanced repeated measures.
Repeated measures are common in clinical trials and epidemiological studies. Designing studies with repeated measures requires reasonably accurate specifications of the variances and correlations to select an appropriate sample size. Underspecifying the variances leads to a sample size that is inade...
| Publicado en: | Statistics in Medicine Vol. 37; no. 3; pp. 375 - 390 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
2/10/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=127334565&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 127334565 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02776715 2DZ jtl: Statistics in Medicine issn: 02776715 maglogo: Y pubinfo: dt: 2/10/2018 vid: 37 iid: 3 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 127334565 127334565 NLM29164637 10.1002/sim.7524 NLM29164637 127334565 ppf: 375 ppct: 15 formats: tig: atl: Internal pilot design for balanced repeated measures. aug: au: Zhang, Xinrui Muller, Keith E. Goodenow, Maureen M. Chi, Yueh‐Yun Chi, Yueh-Yun affil: Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA sug: subj: Sample Size Linear Regression Multivariate Analysis Prospective Studies Pilot Studies Clinical Trials Computer Simulation Statistics Study Design Impact of Events Scale Scales ab: Repeated measures are common in clinical trials and epidemiological studies. Designing studies with repeated measures requires reasonably accurate specifications of the variances and correlations to select an appropriate sample size. Underspecifying the variances leads to a sample size that is inadequate to detect a meaningful scientific difference, while overspecifying the variances results in an unnecessarily large sample size. Both lead to wasting resources and placing study participants in unwarranted risk. An internal pilot design allows sample size recalculation based on estimates of the nuisance parameters in the covariance matrix. We provide the theoretical results that account for the stochastic nature of the final sample size in a common class of linear mixed models. The results are useful for designing studies with repeated measures and balanced design. Simulations examine the impact of misspecification of the covariance matrix and demonstrate the accuracy of the approximations in controlling the type I error rate and achieving the target power. The proposed methods are applied to a longitudinal study assessing early antiretroviral therapy for youth living with HIV. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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