On Inference in Parametric Survival Data Models

Conditional inference in parametric models

This paper presents a new approach to conditional inference, based on the simulation of samples conditioned by a statistics of the data. Also an explicit expression for the approximation of the conditional likelihood of long runs of the sample given the observed statistics is provided. It is shown that when the conditioning statistics is sufficient for a given parameter, the approximating densi...

Semi-parametric Inference for Copula Models for Dependently Truncated Data

Semi-parametric Inference for Copula Models for Truncated Data

We investigate the dependent relationship between two failure time variables that truncate each other. Chaieb, Rivest, and Abdous (2006) proposed a semiparametric model under the so-called “semi-survival” Archimedean-copula assumption and discussed estimation of the association parameter, the truncation probability, and the marginal functions. Here the same model assumption is adopted but diffe...

Supplementary Materials to “Combining parametric, semi-parametric, and non-parametric survival models with stacked survival models”

Section 1 demonstrates the connection between the Brier Score in the absence of censoring versus the inverse probability-of-censoring weighted Brier Score. Section 2 derives the meansquared error decomposition presented in Section 3 of the main paper, and presents illustrations and examples regarding the impact of candidate survival models on performance. In addition, a simple example illustrat...

Combining parametric, semi-parametric, and non-parametric survival models with stacked survival models.

For estimating conditional survival functions, non-parametric estimators can be preferred to parametric and semi-parametric estimators due to relaxed assumptions that enable robust estimation. Yet, even when misspecified, parametric and semi-parametric estimators can possess better operating characteristics in small sample sizes due to smaller variance than non-parametric estimators. Fundamenta...