First-hitting-time Based Threshold Regressions for Lifetime Data: with Applications
vendredi 6 décembre 2013, 11h00 - 12h00
Cox regression methods are well-known. It has, however, a strong proportional hazards assumption. In many medical contexts, a disease progresses until a failure event (such as death) is triggered when the health level first reaches a failure threshold. I will present the Threshold Regression (TR) model for the health process that requires few assumptions and, hence, is quite general in its potential application. Both parametric and distribution-free methods for estimations and predictions using the TR models are derived. Case examples are presented that demonstrate the methodology and its practical use. The methodology provides medical researchers and biostatisticians with new and robust statistical tools for estimating treatment effects and assessing a survivor?s remaining life.
This is a joint work with G.A. Whitmore of McGill University.