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

Correcting for nonrandom ascertainment in generalized linear mixed models (GLMMs), fitted using Gibbs sampling.

Genetic epidemiology - 1 Jan 2003

Burton Paul R

Abstract excerpt

Gibbs sampling-based generalized linear mixed models (GLMMs) provide a convenient and flexible way to extend variance components models for multivariate normally distributed continuous traits to other classes of phenotype. This includes binary traits and right-censored failure times such as age-at-onset data. The approach has applications in many areas of genetic epidemiology. However, the required GLMMs are...

Read the complete abstract on PubMed

Topics

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

Share to Analysis of Variance
Share to Bias
Share to Genetic Diseases, Inborn

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Linear Models

Share to Markov Chains

Share to Monte Carlo Method

Share to Predictive Value of Tests

Share to Sampling Studies

Source

Identifiers

PMID: 12508253
DOI: 10.1002/gepi.10206

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Correcting for nonrandom ascertainment in generalized linear mixed models (GLMMs), fitted using Gibbs sampling.PMID 12508253Read ↗

Variance components analysis for pedigree-based censored survival data using generalized linear mixed models (GLMMs) and Gibbs sampling in BUGS.Semantic proximity Read ↗

Genetic variance components analysis for binary phenotypes using generalized linear mixed models (GLMMs) and Gibbs sampling.Semantic proximity Read ↗

Mixed Model Association with Family-Biased Case-Control Ascertainment.Semantic proximity Read ↗

Ascertainment adjustment in complex diseases.Semantic proximity Read ↗

Mixed model with correction for case-control ascertainment increases association power.Semantic proximity Read ↗

Mixed Model with Correction for Case-Control Ascertainment Increases Association PowerSemantic proximity Read ↗

Estimation of genetic effects in multiple cases family studies using penalized maximum likelihood methodology.Semantic proximity Read ↗

Unbiased discordant sib-pair tests when parental genotypes are missing.Semantic proximity Read ↗

Penalized linear mixed models for structured genetic data.Semantic proximity Read ↗

Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.Semantic proximity Read ↗

A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information.Semantic proximity Read ↗

Bias and efficiency in family-based gene-characterization studies: conditional, prospective, retrospective, and joint likelihoods.Semantic proximity Read ↗

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