Biometrical modeling of twin and family data in Stata
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.
When requesting a correction, please mention this item's handle: RePEc:boc:dsug10:01. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.