Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data.

Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data. Research Abstract Details 

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Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data. Abstract Text:

Matthew J Gurka,Christopher S Coffey,Keith E Muller,Matthew J Gurka,Christopher S Coffey,Keith E Muller,

An internal pilot design uses interim sample size analysis, without interim data analysis, to adjust the final number of observations. The approach helps to choose a sample size sufficiently large (to achieve the statistical power desired), but not too large (which would waste money and time). We report on recent research in cerebral vascular tortuosity (curvature in three dimensions) which would benefit greatly from internal pilots due to uncertainty in the parameters of the covariance matrix used for study planning. Unfortunately, observations correlated across the four regions of the brain and small sample sizes preclude using existing methods. However, as in a wide range of medical imaging studies, tortuosity data have no missing or mistimed data, a factorial within-subject design, the same between-subject design for all responses, and a Gaussian distribution with compound symmetry. For such restricted models, we extend exact, small sample univariate methods for internal pilots to linear mixed models with any between-subject design (not just two groups). Planning a new tortuosity study illustrates how the new methods help to avoid sample sizes that are too small or too large while still controlling the type I error rate.

Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data. Publishing Authors By Initials

MJ Gurka,CS Coffey,KE Muller,MJ Gurka,CS Coffey,KE Muller,

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Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Statistics in medicine

VOLUME: 26

Page Numbers: 4083-99

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ISSN: 0277-6715

DAY: 30

MONTH: Sep

YEAR: 2007

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LANGUAGE: eng

NlmUniqueID: 8215016

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Grant and Affiliation Information for Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data.

AFFILIATION: Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia School of Medicine, P.O. Box 800717, Charlottesville, VA 22908-0717, USA. mgurka@virginia.edu

Country: England

AGENCY: United States NIEHS

GRANT: T32-ES07018

ACRONYM: ES

MEDLINETA: Stat Med

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