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A Comparison of Methods of Fitting Models to Twin Data
Author(s) -
Huggins R.M.,
Loesch D.Z.,
Hoang N.H.
Publication year - 1998
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00015
Subject(s) - mathematics , multivariate statistics , statistics , variance components , multivariate normal distribution , variance (accounting) , covariance matrix , sample (material) , covariance , raw data , multivariate analysis of variance , maximum likelihood , chemistry , accounting , chromatography , business
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.