ArticleBehavior genetics2016
Applying Multivariate Discrete Distributions to Genetically Informative Count Data.
Article in Behavior genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Notes on Three Decades of Methodology Workshops.Behavior genetics · 2021Article
- Multilevel Modeling in Classical Twin and Modern Molecular Behavior Genetics.Behavior genetics · 2021Article
- Overcoming the Challenges to Enhancing Experimental Plant Biology With Computational Modeling.Frontiers in plant science · 2021Review
- A robust and unified framework for estimating heritability in twin studies using generalized estimating equations.Statistics in medicine · 2020Article
- Adolescent Externalizing Psychopathology and Its Prospective Relationship to Marijuana Use Development from Age 14 to 30: Replication Across Independent Longitudinal Twin Samples.Behavior genetics · 2020Article
- Multivariate normal maximum likelihood with both ordinal and continuous variables, and data missing at random.Behavior research methods · 2018Article
- Parent-Offspring Resemblance for Drinking Behaviors in a Longitudinal Twin Sample.Journal of studies on alcohol and drugs · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
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 from a skewed discrete distribution, recovery of twin correlations and proportions of additive genetic and common environment variance was generally poor for the Normal, Lognormal and Ordinal models, but good for the two discrete models. Sex-separate applications to substance-use data from twins in the Minnesota Twin Family Study showed superior performance of two discrete models. The new methods are implemented using R and OpenMx and are freely available.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.