A Warning About Using Predicted Values From Regression Models for Epidemiologic Inquiry

Elizabeth L. Ogburn, Kara E. Rudolph, Rachel Morello-Frosch, Amber Khan, Joan A. Casey

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In many settings, researchers may not have direct access to data on 1 or more variables needed for an analysis and instead may use regression-based estimates of those variables. Using such estimates in place of original data, however, introduces complications and can result in uninterpretable analyses. In simulations and observational data, we illustrate the issues that arise when an average treatment effect is estimated from data where the outcome of interest is predicted from an auxiliary model. We show that bias in any direction can result, under both the null and alternative hypotheses.

Original languageEnglish (US)
Pages (from-to)1142-1147
Number of pages6
JournalAmerican journal of epidemiology
Volume190
Issue number6
DOIs
StatePublished - Jun 1 2021

Keywords

  • imputation
  • measurement error
  • proxy variables

ASJC Scopus subject areas

  • Epidemiology

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