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\centerline{\bf STANFORD UNIVERSITY}
\centerline{\bf DEPARTMENT OF STATISTICS}
\centerline{\big Joint Statistics/Biostatistics Seminar}
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\centerline{ Sequoia Hall, Room 200}
\centerline{4:15 p.m., Thursday, May 16, 2002}


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\centerline{\sl Heping Zhang}
\centerline{\sl Dept of Epidemiology and Public Health}
\centerline{\sl School of Medicine, Yale University}
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\centerline{\bf A Latent Variable Model of Segregation Analysis for Ordinal Traits}

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Many health conditions including cancer and psychiatric disorders are 
believed to have a complex genetic basis, and genes and environmental 
factors are likely to interact one another in the presence and severity of 
these conditions. Assessing familial aggregation and inheritability of 
diseases is a classic topic of genetic epidemiology, which is commonly 
referred to as segregation analysis. While it is routine to conduct such 
analyses for quantitative and dichotomous traits, there do not exist 
methods and software that accommodate ordinal traits. To this end, we 
propose a latent variable model by extending the work of Zhang and 
Merikangas (1999) who examined binary traits. The advantage of this latent 
variable model is its flexibility to include environmental factors 
(usually represented by covariates) and its potential to allow 
gene-environment interactions. The model building employs the EM algorithm 
for maximization and a peeling algorithm for computational efficiency. The 
statistical inference can be made based on the asymptotic theory, a 
permutation procedure as well as simulation studies. At the end, I will 
use this model to analyze the familial transmission of alcoholism.

This is a joint work with Rui Feng, Hongtu Zhu, and Kathleen Merikangas. 



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