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\centerline{\bf STANFORD UNIVERSITY}
\centerline{\bf DEPARTMENT OF STATISTICS}
\centerline{\big DEPARTMENTAL SEMINAR}
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\centerline{4:15 p.m., Tuesday, October 21, 2003}
\centerline{Sequoia Hall Room 200}
\centerline{(Cookies at 3:45 in 1st Floor Lounge)}

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\centerline{\sl Hongzhe Li}
\centerline{\sl Rowe Program in Human Genetics}
\centerline{\sl UC Davis School of Medicine}
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\centerline{\bf The Additive Genetic Gamma Frailty Models for Genetic 
Linkage and Association Analysis }
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Abstract:

Many complex human diseases are due to multiple disease genes and
both genetic and environmental risk factors. These diseases often
also show variable age of disease onset. In order to incorporate
both covariates and age of onset information into genetic
analysis, we define an additive genetic gamma frailty model
constructed based on the inheritance vectors. Within this
modelling framework, we derive a retrospective likelihood ratio
test for linkage and a score test for  genetic association in the
linked region using sibships data. Such tests can incorporate both
affected and unaffected sibs, environmental covariates and age at
disease onset or censoring information, and therefore provide a
practical solution to mapping genes for complex diseases with
variable age of onset. Simulation studies indicate that the
proposed methods have correct type 1 error rates and perform
better than the commonly used methods for linkage or association
analysis. In addition, both power and type 1 error rates are quite
robust to modest misspecification of the baseline hazard function.
We further demonstrate the methods using the simulated data set
from GAW12 and a real data set of affected sib pairs of prostate
cancer.

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