uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
Covariance component models for multivariate binary traits in family data analysis
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Psychiatry, Ulleråker, University Hospital.
Show others and affiliations
2008 (English)In: Statistics in Medicine, ISSN 0277-6715, Vol. 27, no 7, 1086-1105 p.Article in journal (Refereed) Published
Abstract [en]

For family studies, there is now an established analytical framework for binary-trait outcomes within the generalized linear mixed models (GLMMs). However, the corresponding analysis of multivariate binary-trait (MBT) outcomes is still limited. Certain diseases, such as schizophrenia and bipolar disorder, have similarities in epidemiological features, risk factor patterns and intermediate phenotypes. To have a better etiological understanding, it is important to investigate the common genetic and environmental factors driving the comorbidity of the diseases. In this paper, we develop a suitable GLMM for MBT outcomes from extended families, such as nuclear, paternal- and maternal-halfsib families. We motivate our problem with real questions from psychiatric epidemiology and demonstrate how different substantive issues of comorbidity between two diseases can be put into the analytical framework.

Place, publisher, year, edition, pages
2008. Vol. 27, no 7, 1086-1105 p.
Keyword [en]
comorbidity, familial aggregation, multivariate binary trait, variance component
National Category
Medical and Health Sciences
URN: urn:nbn:se:uu:diva-15919DOI: 10.1002/sim.2996ISI: 000254678900010OAI: oai:DiVA.org:uu-15919DiVA: diva2:43690
Available from: 2008-03-18 Created: 2008-03-18Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Hultman, Christina M
By organisation
Psychiatry, Ulleråker, University Hospital
In the same journal
Statistics in Medicine
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 141 hits
ReferencesLink to record
Permanent link

Direct link