Deb Sinha
Department of Biometry, Medical University of South Carolina
"Bayesian Analysis of Survival Data with a Surviving Fraction"
Survival data with a cured fraction commonly arises in cancer and
other clinical trials, in which patients are considered `cured" after
sufficient follow-up and in reliability studies when a machine may not
fail during its technological lifetime. For modeling such data, we
consider a new latent variable method which has useful properties for
Bayesian purposes. We also compare our model with currently popular
mixture model. We present extensions of our model to multivariate
setting and to accelerated testing. Our methodologies are illustrated
through the analyses of some cancer clinical trials data and
reliability experiment involving highly reliable circuits.
Back to Colloquium Series