Abstract
In studies of the genetic basis for chronic conditions, interest routinely lies in the within-family dependence in disease status. When probands are selected from disease registries and their respective families are recruited, a variety of ascertainment bias-corrected methods of inference are available which are typically based on models for correlated binary data. This approach inadequately deals with the ages family members are at the time of assessment and hence the variation in the time at risk among participants. We consider copula-based models for assessing the within-family dependence in the disease onset time and disease progression, based on right-censored and current status observation of the onset times for non-probands. These models are also used to examine the factors influencing the commonly used measures of within-family dependence for correlated binary response to address parent of origin hypotheses. The methods are applied to data from a family study at the University of Toronto Psoriatic Arthritis Clinic.
Joint work with Yujie Zhong, University of Waterloo.