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Biometrical modeling of twin and family data in Stata

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  • Sophia Rabe-Hesketh

    (University of California–Berkeley)

Abstract

Data on twins or on other types of family structures (for example, nuclear families, siblings, cousins) can be used to estimate the proportion of variability in observed traits (or phenotypes) that is due to genes. The models are essentially multivariate regression models with residual covariance structures dictated by Mendelian genetics. Usually, specialized software for structural equation modeling is used. However, the required covariance structures can also be produced using mixed models and by specifying an appropriate design matrix for the random part of the model. Stata’s xtmixed command can then be used to estimate the models. For binary phenotypes, such as diabetes, the appropriate probit models can be estimated using gllamm.

Suggested Citation

  • Sophia Rabe-Hesketh, 2010. "Biometrical modeling of twin and family data in Stata," German Stata Users' Group Meetings 2010 01, Stata Users Group.
    • Handle: RePEc:boc:dsug10:01
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    Cited by:

    1. Rabe, Birgitta & Nicoletti, Cheti, 2010. "Inequality in pupils’ educational attainment: how much do family, sibling type and neighbourhood matter?," ISER Working Paper Series 2010-26, Institute for Social and Economic Research.

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