RT Journal Article
T1 Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.
A1 Agogo, George O
A1 der Voet, Hilko van
A1 Veer, Pieter Van't
A1 Ferrari, Pietro
A1 Leenders, Max
A1 Muller, David C
A1 Sánchez-Cantalejo, Emilio
A1 Bamia, Christina
A1 Braaten, Tonje
A1 Knüppel, Sven
A1 Johansson, Ingegerd
A1 van Eeuwijk, Fred A
A1 Boshuizen, Hendriek
K1 Dieta
K1 Estudios Epidemiológicos
K1 Estudios Longitudinales
K1 Neoplasias
K1 Evaluación Nutricional
K1 Estudios Prospectivos
AB In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.
PB Public Library of Science
YR 2014
FD 2014-11-17
LK http://hdl.handle.net/10668/1908
UL http://hdl.handle.net/10668/1908
LA en
NO Agogo GO, der Voet Hv, Veer PV, Ferrari P, Leenders M, Muller DC, et al. Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study. PLoS ONE 2014; 9(11):e113160
NO Journal Article;
DS RISalud
RD Apr 19, 2025