Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A general framework for studying genetic effects and gene-environment interactions with missing data.

Biostatistics (Oxford, England) - 1 Oct 2010

Hu Y J, Lin D Y, Zeng D

Abstract excerpt

Missing data arise in genetic association studies when genotypes are unknown or when haplotypes are of direct interest. We provide a general likelihood-based framework for making inference on genetic effects and gene-environment interactions with such missing data. We allow genetic and environmen...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biostatistics
Share to Cysteine Endopeptidases
Share to Disease

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Environment

Share to Likelihood Functions

Share to Receptors, Nicotinic

Share to Regression Analysis

Share to Smoking

Source

Open in PubMed Open full text

Identifiers

PMID: 20348396
DOI: 10.1093/biostatistics/kxq015
PMCID: PMC3294269

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026. Prepared record publication-20348396-2026-09-04.2. Manifest publication-graph-cohort-2026-09-04.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A general framework for studying genetic effects and gene-environment interactions with missing data.PMID 20348396Read ↗

Maximum likelihood estimation of haplotype effects and haplotype-environment interactions in association studies.Semantic proximity Read ↗

Simple and efficient analysis of disease association with missing genotype data.Semantic proximity Read ↗

Analysis of case-control studies of genetic and environmental factors with missing genetic information and haplotype-phase ambiguity.Semantic proximity Read ↗

Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study.Semantic proximity Read ↗

A general framework for integrative analysis of incomplete multiomics data.Semantic proximity Read ↗

LFMM 2.0: Latent factor models for confounder adjustment in genome and epigenome-wide association studiesSemantic proximity Read ↗

Efficient semiparametric estimation of haplotype-disease associations in case-cohort and nested case-control studies.Semantic proximity Read ↗

Case-sibling studies that acknowledge unstudied parents and permit the inclusion of unmatched individuals.Semantic proximity Read ↗

Reducing Information and Selection Bias in EHR-Linked Biobanks via Genetics-Informed Multiple Imputation and Sample WeightingSemantic proximity Read ↗

Simultaneous Modeling of Disease Status and Clinical Phenotypes To Increase Power in Genome-Wide Association Studies.Semantic proximity Read ↗

A Likelihood-Based Approach for Missing Genotype Data.Semantic proximity Read ↗

CERAMIC: Case-Control Association Testing in Samples with Related Individuals, Based on Retrospective Mixed Model Analysis with Adjustment for Covariates.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.