Semiparametric Maximum Likelihood Methods for Analyzing Genetic and Environmental Effects with Case‐Control Mother–Child Pair Data

DOI10.1111/j.1541-0420.2011.01728.xzbMath1271.62251OpenAlexW2061525722WikidataQ34269732 ScholiaQ34269732MaRDI QIDQ4649067

Dongyu Lin, Jinbo Chen, Hagit Hochner

Publication date: 19 November 2012

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2011.01728.x

zbMATH Keywords

profile likelihoodgenessemiparametric maximum likelihoodenvironment interactionsjoint genetic and environmental effectsmaternal genetic effectsoffspring genetic effects

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Generalized linear models (logistic models) (62J12)

Related Items (3)

An efficient and computationally robust statistical method for analyzing case-control mother-offspring pair genetic association studies ⋮ Semiparametric nonlinear regression for detecting gene and environment interactions ⋮ Asymptotic properties of a component-wise ARH(1) plug-in predictor

Cites Work

• Large sample theory for semiparametric regression models with two-phase, outcome dependent sampling.
• Exploiting Gene‐Environment Independence for Analysis of Case–Control Studies: An Empirical Bayes‐Type Shrinkage Estimator to Trade‐Off between Bias and Efficiency
• Logistic disease incidence models and case-control studies
• Fitting regression models to case-control data by maximum likelihood
• Shrinkage Estimators for Robust and Efficient Inference in Haplotype-Based Case-Control Studies
• Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies
• Likelihood-Based Inference on Haplotype Effects in Genetic Association Studies
• A Generalization of Sampling Without Replacement From a Finite Universe

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