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Nonrandom sampling in genetic epidemiology: Maximum likelihood methods for multifactorial analysis of quantitative data ascertained through truncation
Author(s) -
Rao D. C.,
Wette R.,
Eaves Lindon J.
Publication year - 1987
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.1370040505
Subject(s) - statistics , truncation (statistics) , sample size determination , mathematics , sampling (signal processing) , maximum likelihood , proband , econometrics , biology , computer science , genetics , mutation , filter (signal processing) , computer vision , gene
Three types of nonrandom sampling of family data are described, and appropriate maximum likelihood methods are proposed for each. The three types arise depending on whether the selection of probands, based on truncation, is applied directly to the phenotypic distribution, to the distribution of a correlated trait, or to the liability distribution of an associated disease. Family data ascertained through random and nonrandom sampling can be analyzed together in a unified approach. Results of a Monte Carlo study are presented that demonstrate the utility of the proposed methods. In particular, likelihood ratio tests of null hypotheses are shown to be distributed as chi‐square, even in samples as small as 50 families (with variable sibship size).