7. Multivariate Decomposition for Hazard Rate Models

By D. Powers, Myeong-Su Yun. Social Science Research Network, 2009

54 citations recorded by the source corpus.

We develop a regression decomposition technique for hazard rate models, where the difference in observed rates is decomposed into components attributable to group differences in characteristics and group differences in effects. The baseline hazard is specified using a piecewise constant exponential model, which leads to convenient estimation based on a Poisson regression model fit to person-period, or split-episode data. This specification allows for a flexible representation of the baseline hazard and provides a straightforward way to introduce time-varying covariates and time-varying effects. We provide computational details underlying the method and apply the technique to the decomposition of the black-white difference in first premarital birth rates into components reflecting characteristics and effect contributions of several predictors, as well as the effect contribution attributable to race differences in the baseline hazard.

Subfields: Demography, Economics and Econometrics, Health

View Paper: https://www.semanticscholar.org/paper/b4c8e2890d617581cbb3d4f3fed585a0e939522b

Citations in the corpus

• Standardization and Control for Confounding in Observational Studies: A Historical Perspective (2015, unknown): “…further development of additive decomposition ideas; for recent reviews see Chevan and Sutherland (2009) for the development in demography and Powers and Yun (2009) for decomposition of hazard rate models and some references to developments in econometrics and to some extent in sociology.”