Assessing Bias and Fit of Global and Local Hazard Models

This article assesses the bias and fit of a hazard rate model by comparing predicted and nonparametric estimates of survivor probabilities, and suggests that a nonproportional local Gompertz model performs better than other models examined.

Abstract

This article assesses the bias and fit of a hazard rate model by comparing predicted and nonparametric estimates of survivor probabilities. These comparisons also generate several diagnostic displays for event history data. We illustrate these diagnostic methods for several global and local hazard models using data on age at first marriage for women from the June 1980 Current Population Survey. Our results suggest that a nonproportional local Gompertz model performs better than other models we examined.