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A Comparison of Methods of Fitting Models to Twin Data

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Data on twins are used to infer a genetic component of variance for various quantitative human characteristics. There are several statistical approaches available to analyze twin data. Here we compare three approaches for fitting variance components models to the relationship between height and bi-illiocristal diameter across ages in a sample of male and female Polish twins aged 8–17. Two of the approaches assume a multivariate normal model for the data, with one basing the likelihood on the raw data and the other using the distribution of the sample covariance matrix. The third approach uses a robust modification of the multivariate normal log-likelihood to downweight abnormal observations. The statistical theory underlying the methods is outlined, and the implementation of the methods is discussed.
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Keywords: computing packages; outliers; twin data

Document Type: Original Article

Affiliations: La Trobe University

Publication date: June 1, 1998

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