An efficient and computationally robust statistical method for analyzing case-control mother-offspring pair genetic association studies

DOI10.1214/19-AOAS1298zbMath1446.62161MaRDI QIDQ2194447

Victoria Arthur, Jinbo Chen, Hong Zhang, Gang Hu, Bhramar Mukherjee, Hagit Hochner

Publication date: 26 August 2020

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1593449316

zbMATH Keywords

saddle point problemprofile likelihoodgenetic associationretrospective likelihoodcase-control mother-offspring pair design

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Measures of association (correlation, canonical correlation, etc.) (62H20) Response surface designs (62K20)

Uses Software

• UNPHASED

Cites Work

• Unnamed Item
• Adjustment of nonconfounding covariates in case-control genetic association studies
• Robust partial likelihood approach for detecting imprinting and maternal effects using case-control families
• Logistic disease incidence models and case-control studies
• Semiparametric Maximum Likelihood Methods for Analyzing Genetic and Environmental Effects with Case‐Control Mother–Child Pair Data
• Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies

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