Regression calibration for logistic regression with multiple surrogates for one exposure

DOI10.1016/j.jspi.2006.01.009zbMath1102.62123OpenAlexW1969876854WikidataQ96592458 ScholiaQ96592458MaRDI QIDQ861211

Ellen A. Eisen, Edie A. Weller, Donald K. Milton, Donna Spiegelman

Publication date: 9 January 2007

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2006.01.009

zbMATH Keywords

asymptotic relative efficiencymeasurement errorexposuremain studymetal working fluidsvalidation study

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items

Regression calibration in air pollution epidemiology with exposure estimated by spatio‐temporal modeling ⋮ QuantifyingR²bias in the presence of measurement error ⋮ Stratified Logrank Test of No Randomized Treatment Effect with Missing Stratum Information ⋮ Approximate and pseudo-likelihood analysis for logistic regression using external validation data to model log exposure ⋮ Censored count data regression with missing censoring information ⋮ A study of regression calibration in a partially observed stratified Cox model ⋮ Multsurr

Uses Software

• SAS
• BLINPLUS
• relibpls8

Cites Work

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• Equivalence of regression calibration methods in main study/external validation study designs
• A Detailed Evaluation of Adjustment Methods for Multiplicative Measurement Error in Linear Regression with Applications in Occupational Epidemiology
• Estimation of Linear and Nonlinear Errors-in-Variables Models Using Validation Data