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Analysis of associations with change in a multivariate outcome variable when baseline is subject to measurement error.

TitleAnalysis of associations with change in a multivariate outcome variable when baseline is subject to measurement error.
Publication TypeJournal Article
Year of Publication2003
AuthorsChambless LE, Davis V
JournalStat Med
Volume22
Issue7
Pagination1041-67
Date Published2003 Apr 15
ISSN0277-6715
KeywordsAlgorithms, Bias, Computer Simulation, Coronary Disease, Humans, Linear Models, Middle Aged, Models, Statistical, Multivariate Analysis, Tunica Intima, Ultrasonography
Abstract

A simple general algorithm is described for correcting for bias caused by measurement error in independent variables in multivariate linear regression. This algorithm, using standard software, is then applied to several approaches to the analysis of change from baseline as a function of baseline value of the outcome measure plus other covariates, any of which might have measurement error. The algorithm may also be used when the independent variables differ by component of the multivariate independent variable. Simulations indicate that under various conditions bias is much reduced, as is mean squared error, and coverage of 95 per cent confidence intervals is good.

DOI10.1002/sim.1352
Alternate JournalStat Med
PubMed ID12652553