A Partially Linear Censored Quantile Regression Model for Unemployment Duration

Censored Regression Quantile (CRQ) methods provide a powerful and flexible approach for the analysis of censored survival data when standard linear models are felt to be appropriate. In many cases however, greater flexibility is desired to go beyond the usual multiple regression paradigm. One area of common interest is that of partially linear models, where one (or more) of the explanatory variables are assumed to act on the response through a non-linear function. Here the CRQ approach (Portnoy, 2003) is extended to such partially linear setting. Basic consistency results are presented. A simulation experiment and analysis of unemployment data example justify the use of the partially linear approach over methods based on the Cox proportional hazards regression model and methods not permitting nonlinearity.