A three-part regression calibration to handle excess zeroes, skewness and heteroscedasticity in adjusting for measurement error in dietary intake data

DOI10.1080/02664763.2020.1845622OpenAlexW3105515725MaRDI QIDQ5085666

George O. Agogo, Alexander K. Muoka

Publication date: 27 June 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1845622

zbMATH Keywords

attenuationtwo-part modelgeneralized gamma modeldietary intake

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• bootstrap

Cites Work

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• A new multivariate measurement error model with zero-inflated dietary data, and its application to dietary assessment
• Reverse attenuation in interaction terms due to covariate measurement error
• A bivariate measurement error model for semicontinuous and continuous variables: Application to nutritional epidemiology
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• A zero-augmented generalized gamma regression calibration to adjust for covariate measurement error: A case of an episodically consumed dietary intake
• Allowing for never and episodic consumers when correcting for error in food record measurements of dietary intake
• Evaluation of a two-part regression calibration to adjust for dietary exposure measurement error in the Cox proportional hazards model: A simulation study
• Predicting renal graft failure using multivariate longitudinal profiles
• Theory & Methods: A zero‐augmented gamma mixed model for longitudinal data with many zeros
• A Two-Part Random-Effects Model for Semicontinuous Longitudinal Data
• Measurement Error in Nonlinear Models
• Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles
• Modeling Data with Excess Zeros and Measurement Error: Application to Evaluating Relationships between Episodically Consumed Foods and Health Outcomes

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