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Measuring familial aggregation by using odds-ratio regression models: Familial Aggregation of Binary Traits by Dr. Kung-Yee Liang; Terri H. Beaty; G. P. Vogler is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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Detection of familial aggregation of a disease is important for studying possible genetic and environmental factors contributing to disease etiology. Accurate quantification of familial aggregation can provide guidance for subsequent, more sophisticated genetic studies. This article presents a statistical model and method for detecting both inter-and intra-class aggregation of a binary trait with family data. The method used here is based on the logistic regression model which incorporates effects of individual covariates while measuring familial aggregation of risk as the odds ratios among classes of relatives. An estimation equation approach is presented where the joint distribution of binary traits among family members need not be fully specified. Data from a genetic epidemiologic study on liver cancer in Shanghai are analyzed for illustration, and reveal strong aggregation of risk even after adjusting for covariates. Effects of non-random sampling and ascertainment bias are also discussed.

Who reads Measuring familial aggregation by using odds-ratio regression models: Familial Aggregation of Binary Traits?

Author

Dr. Kung-Yee Liang; Terri H. Beaty; G. P. Vogler

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0741-0395)

Published

1990

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)