ArticleGenetic epidemiology2010
Variance-components methods for linkage and association analysis of ordinal traits in general pedigrees.
Article in Genetic epidemiology, 2010. 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
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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.
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Who cites it
7 citing papers in PubMed.
- Genome-wide association studies and QTL mapping for traits deviating from normal distribution.National science review · 2026Article
- Genetic association tests in family samples for multi-category phenotypes.BMC genomics · 2021Article
- A permutation method for detecting trend correlations in rare variant association studies.Genetics research · 2019Article
- Association detection between ordinal trait and rare variants based on adaptive combination of P values.Journal of human genetics · 2018Article
- Efficient semiparametric estimation of short-term and long-term hazard ratios with right-censored data.Biometrics · 2013Article
- An efficient hierarchical generalized linear mixed model for mapping QTL of ordinal traits in crop cultivars.PloS one · 2013Article
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Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Many complex human diseases such as alcoholism and cancer are rated on ordinal scales. Well-developed statistical methods for the genetic mapping of quantitative traits may not be appropriate for ordinal traits. We propose a class of variance-component models for the joint linkage and association analysis of ordinal traits. The proposed models accommodate arbitrary pedigrees and allow covariates and gene-environment interactions. We develop efficient likelihood-based inference procedures under the proposed models. The maximum likelihood estimators are approximately unbiased, normally distributed, and statistically efficient. Extensive simulation studies demonstrate that the proposed methods perform well in practical situations. An application to data from the Collaborative Study on the Genetics of Alcoholism is provided.
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