Survival analysis with incomplete genetic data

DOI10.1007/S10985-013-9262-8zbMath1322.62317OpenAlexW2045779137WikidataQ30636571 ScholiaQ30636571MaRDI QIDQ746521

D. Y. Lin

Publication date: 16 October 2015

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3806886

zbMATH Keywords

haplotypescensoringsingle nucleotide polymorphismscase-cohort designgenome-wide association studiesnext-generation sequencingnonparametric likelihoodcase-control designtwo-phase studywomen's health initiative

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Genetics and epigenetics (92D10)

Cites Work

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• A general framework for studying genetic effects and gene-environment interactions with missing data
• Efficient semiparametric estimation of haplotype-disease associations in case-cohort and nested case-control studies
• A case-cohort design for epidemiologic cohort studies and disease prevention trials
• Logistic disease incidence models and case-control studies
• On Profile Likelihood
• Likelihood-Based Inference on Haplotype Effects in Genetic Association Studies

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