Measurement error in life history data - ARCHIVED

Articles and reports: 11-522-X200600110397


In practice it often happens that some collected data are subject to measurement error. Sometimes covariates (or risk factors) of interest may be difficult to observe precisely due to physical location or cost. Sometimes it is impossible to measure covariates accurately due to the nature of the covariates. In other situations, a covariate may represent an average of a certain quantity over time, and any practical way of measuring such a quantity necessarily features measurement error. When carrying out statistical inference in such settings, it is important to account for the effects of mismeasured covariates; otherwise, erroneous or even misleading results may be produced. In this paper, we discuss several measurement error examples arising in distinct contexts. Specific attention is focused on survival data with covariates subject to measurement error. We discuss a simulation-extrapolation method for adjusting for measurement error effects. A simulation study is reported.

Issue Number: 2006001
Author(s): He, Wenqing; Yi, Grace
FormatRelease dateMore information
CD-ROMMarch 17, 2008
PDFMarch 17, 2008