Maximum Likelihood Inference On A Mixed Conditionally and Marginally Specified Regression Model for Genetic Epidemiologic Studies with Two-Phase Sampling

DOI10.1111/J.1467-9868.2007.00580.XzbMath1120.62096OpenAlexW2129138507MaRDI QIDQ5422021

Nilanjan Chatterjee, Yi-Hau Chen

Publication date: 26 October 2007

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/j.1467-9868.2007.00580.x

zbMATH Keywords

case-control studiesmissing dataoutcome dependent sampling

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Sampling theory, sample surveys (62D05) Genetics and epigenetics (92D10) Estimation in survival analysis and censored data (62N02)

Related Items (7)

Genetic model for longitudinal studies of aging, health, and longevity and its potential application to incomplete data ⋮ Binary response models with \(M\)-phase case-control data ⋮ Analysis of an outcome-dependent enriched sample: hypothesis tests ⋮ Semiparametric Maximum Likelihood Estimation With Two-Phase Stratified Case-Control Sampling ⋮ Bayesian semiparametric analysis for two-phase studies of gene-environment interaction ⋮ The Semiparametric Case-Only Estimator ⋮ Semiparametric Estimation Exploiting Covariate Independence in Two‐Phase Randomized Trials

Cites Work

• Binary Regression Using an Extended Beta-Binomial Distribution, With Discussion of Correlation Induced by Covariate Measurement Errors
• On the Unique Consistent Solution to the Likelihood Equations
• Semiparametric Methods for Response-Selective and Missing Data Problems in Regression
• Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
• Design and Analysis of Two-Phase Studies with Binary Outcome Applied to Wilms Tumour Prognosis
• The analysis of retrospective family studies
• Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies
• An Estimated Likelihood Method for Continuous Outcome Regression Models With Outcome-Dependent Sampling
• Contribution to the Theory of Sampling Human Populations
• A Generalization of Sampling Without Replacement From a Finite Universe

This page was built for publication: Maximum Likelihood Inference On A Mixed Conditionally and Marginally Specified Regression Model for Genetic Epidemiologic Studies with Two-Phase Sampling