Estimating the effect of a predictor measured by two informants on a continuous outcome: a comparison of methods.

ABSTRACT: Investigators sometimes use information obtained from multiple informants about a given variable. We focus on estimating the effect of a predictor on a continuous outcome, when that (true) predictor cannot be observed directly but is measured by 2 informants. We describe various approaches to using information from 2 informants to estimate a regression or correlation coefficient for the effect of the (true) predictor on the outcome. These approaches include methods we refer to as single informant, simple average, optimal weighted average, principal components analysis, and classical measurement error. Each of these 5 methods effectively uses a weighted average of the informants' reports as a proxy for the true predictor in calculating the correlation or regression coefficient. We compare t

SUBMITTER: Javaras KN 

PROVIDER: S-EPMC3073873 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature