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Biostatistics 4:195-206 (2003)
© 2003 Oxford University Press

A multivariate family-based association test using generalized estimating equations: FBAT-GEE

Christoph Lange*, Edwin K. Silverman, Xin Xu, Scott T. Weiss and Nan M. Laird

Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA clange{at}hsph.harvard.edu
Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA
Program of Population Genetics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA
Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA
Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA

*To whom correspondence should be addressed

In this paper we propose a multivariate extension of family-based association tests based on generalized estimating equations. The test can be applied to multiple phenotypes and to phenotypic data obtained in longitudinal studies without making any distributional assumptions for the phenotypic observations. Methods for handling missing phenotypic information are discussed. Further, we compare the power of the multivariate test with permutation tests and with using separate tests for each outcome which are adjusted for multiple testing. Application of the proposed test to an asthma study illustrates the power of the approach.

Keywords: Family-based association tests (FBATs); GEE; Genetic association tests; Multivariate phenotypes


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