Moment adjusted imputation for multivariate measurement error data with applications to logistic regression

DOI10.1016/j.csda.2013.04.017zbMath1471.62194OpenAlexW2028189019WikidataQ30670439 ScholiaQ30670439MaRDI QIDQ1615079

Laine Thomas, Leonard A. Stefanski, Marie Davidian

Publication date: 2 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3780432

zbMATH Keywords

logistic regressionregression calibrationmultivariate measurement errormoment adjusted imputation

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Generalized linear models (logistic models) (62J12) General nonlinear regression (62J02)

Uses Software

• BLINPLUS
• relibpls8

Cites Work

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• Density estimation with heteroscedastic error
• Covariate measurement error in logistic regression
• On deconvolution with repeated measurements
• A Moment-Adjusted Imputation Method for Measurement Error Models
• A New Method for Dealing with Measurement Error in Explanatory Variables of Regression Models
• Deconvolving kernel density estimators
• Unbiased estimation of a nonlinear function a normal mean with application to measurement err oorf models
• Optimal Rates of Convergence for Deconvolving a Density
• Triple-goal Estimates in Two-stage Hierarchical Models
• Low Order Approximations in Deconvolution and Regression with Errors in Variables
• Measurement Error in Nonlinear Models

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