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

Applying Multivariate Discrete Distributions to Genetically Informative Count Data.

Behavior genetics - 1 Mar 2016

Kirkpatrick Robert M, Neale Michael C

Abstract excerpt

We present a novel method of conducting biometric analysis of twin data when the phenotypes are integer-valued counts, which often show an L-shaped distribution. Monte Carlo simulation is used to compare five likelihood-based approaches to modeling: our multivariate discrete method, when its distributional assumptions are correct, when they are incorrect, and three other methods in common use. With data simulated...

Read the complete abstract on PubMed

Topics

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

Share to Computer Simulation
Share to Databases, Genetic
Share to Family

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Models, Genetic

Share to Monte Carlo Method

Share to Multivariate Analysis

Share to Substance-Related Disorders

Source

Open in PubMed Open full text

Identifiers

PMID: 26497008
DOI: 10.1007/s10519-015-9757-z
PMCID: PMC4752908

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Applying Multivariate Discrete Distributions to Genetically Informative Count Data.PMID 26497008Read ↗

Operating Characteristics of Statistical Methods for Detecting Gene-by-Measured Environment Interaction in the Presence of Gene-Environment Correlation under Violations of Distributional Assumptions.Semantic proximity Read ↗

Using the Mplus computer program to estimate models for continuous and categorical data from twins.Semantic proximity Read ↗

A generalized Defries-Fulker regression framework for the analysis of twin data.Semantic proximity Read ↗

Univariate analysis of dichotomous or ordinal data from twin pairs: a simulation study comparing structural equation modeling and logistic regression.Semantic proximity Read ↗

A new method to account for missing data in case-parent triad studies.Semantic proximity Read ↗

An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research.Semantic proximity Read ↗

An integrated phenomic approach to multivariate allelic association.Semantic proximity Read ↗

Using Multimodel Inference/Model Averaging to Model Causes of Covariation Between Variables in Twins.Semantic proximity Read ↗

Evaluation of analyses of univariate discrete twin data.Semantic proximity Read ↗

Advances in behavioral genetics modeling using Mplus: applications of factor mixture modeling to twin data.Semantic proximity Read ↗

Longitudinal modeling of genetic and environmental influences on self-reported availability of psychoactive substances: alcohol, cigarettes, marijuana, cocaine and stimulants.Semantic proximity Read ↗

A note on issues in meta-analysis for behavioral genetic studies using categorical phenotypes.Semantic proximity Read ↗

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