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Issues in Implementing Regression Calibration Analyses.

TitleIssues in Implementing Regression Calibration Analyses.
Publication TypePublication
AuthorsBoe LA, Shaw PA, Midthune D, Gustafson P, Kipnis V, Park E, Sotres-Alvarez D, Freedman L, Initiative OBehalf Of
JournalAm J Epidemiol
Date Published2023 Aug 04
Keywordsbias, calibration, Humans, Public Health, regression analysis

Regression calibration is a popular approach for correcting biases in estimated regression parameters when exposure variables are measured with error. This approach involves building a calibration equation to estimate the value of the unknown true exposure given the error-prone measurement and other covariates. The estimated, or calibrated, exposure is then substituted for the unknown true exposure in the health outcome regression model. When used properly, regression calibration can greatly reduce the bias induced by exposure measurement error. Here, we first provide an overview of the statistical framework for regression calibration, specifically discussing how a special type of error, called Berkson error, arises in the estimated exposure. We then present practical issues to consider when applying regression calibration, including: 1) how to develop the calibration equation and which covariates to include; 2) valid ways to calculate standard errors of estimated regression coefficients; and 3) problems arising if one of the covariates in the calibration model is a mediator of the relationship between the exposure and outcome. Throughout, we provide illustrative examples using data from the Hispanic Community Health Study/Study of Latinos (United States, 2008-2011) and simulations. We conclude with recommendations for how to perform regression calibration.

Alternate JournalAm J Epidemiol
PubMed ID37092245
PubMed Central IDPMC10666971
Grant ListR01 AI131771 / AI / NIAID NIH HHS / United States
75N92019D00010 / HL / NHLBI NIH HHS / United States
N01HC65236 / HL / NHLBI NIH HHS / United States
N01HC65235 / HL / NHLBI NIH HHS / United States
N01HC65234 / HL / NHLBI NIH HHS / United States
P30 CA008748 / CA / NCI NIH HHS / United States
N01HC65233 / HL / NHLBI NIH HHS / United States
N01HC65237 / HL / NHLBI NIH HHS / United States
R37 AI131771 / AI / NIAID NIH HHS / United States
Manuscript Lead/Corresponding Author Affiliation: 
Affiliated Investigator - Not at HCHS/SOL site
Manuscript Affiliation: 
Coordinating Center - Collaborative Studies Coordinating Center - UNC at Chapel Hill
Manuscript Status: