Expected Estimating Equations to Accommodate Covariate Measurement Error
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Publication:4505998
DOI10.1111/1467-9868.00247zbMath0963.62065OpenAlexW2099811086MaRDI QIDQ4505998
C. Y. Wang, Margaret Sullivan Pepe
Publication date: 3 July 2001
Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/1467-9868.00247
longitudinal datamaximum likelihoodlogistic regressionmissing datageneralized estimating equationregression calibration
Asymptotic distribution theory in statistics (62E20) Generalized linear models (logistic models) (62J12)
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APPLIED REGRESSION ANALYSIS BIBLIOGRAPHY UPDATE 2000–2001 ⋮ Likelihood-based kernel estimation in semiparametric errors-in-covariables models with validation data ⋮ Empirical likelihood inference for longitudinal data with covariate measurement errors: an application to the LEAN study ⋮ Optimal model averaging for semiparametric partially linear models with measurement errors ⋮ Inference in generalized linear regression models with a censored covariate ⋮ Heteroscedastic mixture transition distribution (HMTD) model ⋮ Bayesian Nonparametric Regression Analysis of Data with Random Effects Covariates from Longitudinal Measurements ⋮ Functional methods for logistic regression on random-effect-coefficients for longitudinal measurements ⋮ Expected Estimating Equations for Missing Data, Measurement Error, and Misclassification, with Application to Longitudinal Nonignorable Missing Data ⋮ Robust estimation in linear regression models for longitudinal data with covariate measurement errors and outliers ⋮ Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates ⋮ Augmented Inverse Probability Weighted Estimator for Cox Missing Covariate Regression ⋮ Imputation for statistical inference with coarse data ⋮ Partially Supervised Learning Using an EM‐Boosting Algorithm
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