Lange Christoph, Silverman Edwin K, Xu Xin, Weiss Scott T, Laird Nan M
Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA.
Biostatistics. 2003 Apr;4(2):195-206. doi: 10.1093/biostatistics/4.2.195.
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.
在本文中，我们基于广义估计方程提出了一种基于家系的关联检验的多变量扩展方法。该检验可应用于多种表型以及纵向研究中获得的表型数据，而无需对表型观测值做任何分布假设。文中讨论了处理缺失表型信息的方法。此外，我们将多变量检验的效能与置换检验以及对每个结局单独进行检验（并针对多重检验进行调整）的效能进行了比较。将所提出的检验应用于一项哮喘研究，说明了该方法的效能。
