We examine a new general class of hazard rate models for survival data, containing a parametric and a nonparametric component. Both can be a mix of a time effect and (possibly time-dependent) marker or covariate effects. A number of well-known models are special cases. In a counting process...

We compare and evaluate two different approaches to estimate overall survival curvesfrom censored data of recurrent events: (1) standard survival time analysis, and (2) a multistate framework that explicitly estimates the mortality rate during censored periods. With both models, we estimate...

This article presents hsmlogit, a new Stata command that estimates multispells discrete time competing risks duration models with unobserved heterogeneity. hsmlogit allows for the estimation of one, two and up to three competing risks, as well as a maximum of ve points of support for the...

Empirical researchers usually prefer statistical models that can be easily estimated using standard software packages. One such model is the sequential binary model with or without normal random effects; such models can be adopted to estimate discrete duration models with unobserved...

This paper shows that popular linear fixed-effects panel-data estimators (first-differences, within-transformation) are biased and inconsistent when applied in a discrete-time hazard setting, that is, one with the outcome variable being a binary dummy indicating an absorbing state, even if the...

The authors model COVID infections and COVID deaths, both reported and implied, for the 50 U.S. states as well as the District of Columbia, and separately for a sample of 33 countries, as a function of pre-existing circumstances that citizens have no ability to control over the short term. These...