Proportional Odds Models with High-Dimensional Data Structure

Model Diagnostics for Proportional and Partial Proportional Odds Models

Proportional Odds and Partial Proportional Odds Models for Ordinal Response Variables

Ordinal regression modelling between proportional odds and non-proportional odds

Boosting proportional hazards models using smoothing splines, with applications to high-dimensional microarray data

MOTIVATION An important area of research in the postgenomics era is to relate high-dimensional genetic or genomic data to various clinical phenotypes of patients. Due to large variability in time to certain clinical events among patients, studying possibly censored survival phenotypes can be more informative than treating the phenotypes as categorical variables. Due to high dimensionality and c...

Inference for a family of survival models encompassing the proportional hazards and proportional odds models.

For survival data regression, the Cox proportional hazards model is the most popular model, but in certain situations the Cox model is inappropriate. Various authors have proposed the proportional odds model as an alternative. Yang and Prentice recently presented a number of easily implemented estimators for the proportional odds model. Here we show how to extend the methods of Yang and Prentic...