Literature DB >> 3567294

Regressive logistic models for familial disease and other binary traits.

G E Bonney.   

Abstract

The simple Markovian structures of dependence, defined previously for continuous traits, are extended here to familial disease and other binary traits through the use of the logistic function. The regressive models so formulated can incorporate explanatory variables and major gene effects for segregation and linkage analyses. Thus, the goals of epidemiology and genetics in the analysis of familial disease can be accomplished in the same computational scheme.

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Year:  1986        PMID: 3567294

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  56 in total

1.  Bias and efficiency in family-based gene-characterization studies: conditional, prospective, retrospective, and joint likelihoods.

Authors:  P Kraft; D C Thomas
Journal:  Am J Hum Genet       Date:  2000-03       Impact factor: 11.025

2.  Individual-specific liability groups in genetic linkage, with applications to kindreds with Li-Fraumeni syndrome.

Authors:  Sanjay Shete; Christopher I Amos; Shih-Jen Hwang; Louise C Strong
Journal:  Am J Hum Genet       Date:  2002-01-30       Impact factor: 11.025

3.  Major recessive gene(s) with considerable residual polygenic effect regulating adult height: confirmation of genomewide scan results for chromosomes 6, 9, and 12.

Authors:  Jianfeng Xu; Eugene R Bleecker; Hajo Jongepier; Timothy D Howard; Gerard H Koppelman; Dirkje S Postma; Deborah A Meyers
Journal:  Am J Hum Genet       Date:  2002-07-15       Impact factor: 11.025

4.  Heritability and segregation analysis of deafness in U.S. Dalmatians.

Authors:  E J Cargill; T R Famula; G M Strain; K E Murphy
Journal:  Genetics       Date:  2004-03       Impact factor: 4.562

Review 5.  Linkage analysis in the next-generation sequencing era.

Authors:  Joan E Bailey-Wilson; Alexander F Wilson
Journal:  Hum Hered       Date:  2011-12-23       Impact factor: 0.444

Review 6.  Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses.

Authors:  M J Sillanpää
Journal:  Heredity (Edinb)       Date:  2010-07-14       Impact factor: 3.821

7.  A logistic regression mixture model for interval mapping of genetic trait loci affecting binary phenotypes.

Authors:  Weiping Deng; Hanfeng Chen; Zhaohai Li
Journal:  Genetics       Date:  2005-11-04       Impact factor: 4.562

8.  Segregation analysis of cancer in families of childhood soft-tissue-sarcoma patients.

Authors:  E D Lustbader; W R Williams; M L Bondy; S Strom; L C Strong
Journal:  Am J Hum Genet       Date:  1992-08       Impact factor: 11.025

9.  Segregation analysis of 1,546 prostate cancer families in Finland shows recessive inheritance.

Authors:  Sanna Pakkanen; Agnes B Baffoe-Bonnie; Mika P Matikainen; Pasi A Koivisto; Teuvo L J Tammela; Snehal Deshmukh; Liang Ou; Joan E Bailey-Wilson; Johanna Schleutker
Journal:  Hum Genet       Date:  2007-01-03       Impact factor: 4.132

10.  Analysis of Incomplete Longitudinal Binary Data-A Combined Markov's Transition and Logistic Model for Non-ignorable Missingness.

Authors:  Francis Erebholo; Paul Bezandry; Victor Apprey; John Kwagyan
Journal:  Appl Appl Math       Date:  2016-06
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