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ABSTRACT Dr. Joanna Shih, National Heart Lung and Blood Institute, National
Institutes of Health
We propose a bivariate discrete survival distribution which allows
flexible modeling of the marginal distributions and yields a constant odds
ratio at any grid point. The distribution can be extended to a
multivariate distribution and is readily generalized to accommodate
covariates in the marginal distributions and pairwise odds ratios. In
addition, we propose a pseudo-likelihood estimation procedure for
estimating the regression coefficients in the marginal models and the
association parameters in the pairwise odds ratios. We evaluate the
performance of the proposed estimation procedure through simulations. For
bivariate data, pseudo-likelihood estimation of the association parameter
has high efficiency. Loss of efficiency in the marginal regression
coefficient estimates is small when the association is not strong. For
both the marginal regression coefficients and the association parameter,
coverage probabilities are close to the 95% nominal level. For
multivariate data, the simulation results show that the parameter
estimates are consistent. Coverage probability for the regression
coefficient in the marginal model is close to the 95% nominal level, but
is slightly less than the nominal level for the association parameter. We
illustrate the proposed methods using a subset of the Framingham Study
data where a significant positive association was found between the
failure times of siblings.
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