Semiparametric Estimation Exploiting Covariate Independence in Two‐Phase Randomized Trials

DOI10.1111/j.1541-0420.2008.01046.xzbMath1159.62331OpenAlexW2114200062WikidataQ33941830 ScholiaQ33941830MaRDI QIDQ3623755

James Y. Dai, Charles Kooperberg, Michael L. LeBlanc

Publication date: 23 April 2009

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2892338

zbMATH Keywords

Newton-Raphson algorithmprofile likelihoodtreatmentestimated likelihoodgene-environment independencecase-only estimatorbiomarker interactions

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02)

Related Items (4)

Two‐stage penalized regression screening to detect biomarker–treatment interactions in randomized clinical trials ⋮ Structures and assumptions: strategies to harness gene \(\times\) gene and gene \(\times\) environment interactions in GWAS ⋮ Augmented case-only designs for randomized clinical trials with failure time endpoints ⋮ Case–control genome-wide joint association study using semiparametric empirical model and approximate Bayes factor

Cites Work

• Unnamed Item
• Large sample theory for semiparametric regression models with two-phase, outcome dependent sampling.
• Logistic regression for two-stage case-control data
• Logistic disease incidence models and case-control studies
• Fitting Logistic Regression Models in Stratified Case-Control Studies
• Inference and missing data
• 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
• Fitting regression models to case-control data by maximum likelihood
• Estimation from truncated lifetime data with supplementary information on covariates and censoring times
• A Pseudoscore Estimator for Regression Problems With Two-Phase Sampling
• A Weighted Estimating Equation for Missing Covariate Data with Properties Similar to Maximum Likelihood
• On Profile Likelihood
• Monte Carlo EM for Missing Covariates in Parametric Regression Models
• A mean score method for missing and auxiliary covariate data in regression models
• Maximum Likelihood Inference On A Mixed Conditionally and Marginally Specified Regression Model for Genetic Epidemiologic Studies with Two-Phase Sampling
• 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

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