The other side of method bias: The perils of distinct source research designs

John Kammeyer-Mueller, Piers D.G. Steel, Alex Rubenstein

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Common source bias has been the focus of much attention. To minimize the problem, researchers have sometimes been advised to take measurements of predictors from one observer and measurements of outcomes from another observer or to use separate occasions of measurement. We propose that these efforts to eliminate biases due to common source variance create serious problems. To demonstrate the problems of using what we term the "distinct sources" measurement design, we provide an integrative review of the literature regarding both contamination and deficiency of measures. Building on this theme, the article uses simulated data to demonstrate how using data from distinct observers or occasions of measurement can distort estimates of predictor importance at least as much as common source variance. Alternative multisource designs are advocated and examined for tractability by simulating various numbers of observations and sources in the research design.

Original languageEnglish (US)
Pages (from-to)294-321
Number of pages28
JournalMultivariate Behavioral Research
Volume45
Issue number2
DOIs
StatePublished - Mar 1 2010

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