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Variance components/major locus likelihood approximation for quantitative, polychotomous, and multivariate data
Author(s) -
Hasstedt Sandra J.
Publication year - 1993
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.1370100302
Subject(s) - univariate , multivariate statistics , locus (genetics) , statistics , biometrics , mathematics , multivariate analysis , computation , econometrics , computer science , biology , genetics , algorithm , artificial intelligence , gene
Pearson [ Philos Trans R Soc Lond [A] 200:1–66, 1903], Mendell and Elston [ Biometrics 30:41–57, 1974], and Rice et al. [ Biometrics 35:451–459, 1979] approximated the likelihood of the multifactorial model on a dichotomous phenotype by a procedure of successive univariate computation and conditioning. Hasstedt [Pap: Pedigree Analysis Package, Rev. 3. 1989] and Demenais [ Am J Hum Genet 49:773–785, 1991] extended the algorithm to include a major locus. Here I extend the algorithm to polychotomous, quantitative, and multivariate phenotypes, add a major locus to the model, and describe and evaluate the accuracy of an approximation of the resulting variance components/major locus model. © 1993 Wiley‐Liss, Inc.