The generalized odd log-logistic-G regression with interval-censored survival data

Abstract

The article proposes a new regression based on the generalized odd log-logistic family for interval-censored data. The survival times are not observed for this type of data, and the event of interest occurs at some random interval. This family can be used in interval modeling since it generalizes some popular lifetime distributions in addition to its ability to present various forms of the risk function. The estimation of the parameters is addressed by the classical and Bayesian methods. We examine the behavior of the estimates for some sample sizes and censorship percentages. Selection criteria, likelihood ratio tests, residual analysis, and graphical techniques assess the goodness of fit of the fitted models. The usefulness of the proposed models is red shown by means of two real data sets.

Keywords:

• Bayesian inference
• generalized odd log-logistic family
• interval-censored data
• regression model
• residual analysis

Mathematics Subject Classification:

• 62N01

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The traceplot corresponding to one or more Markov chains provides a visual way to inspect sampling behavior and assess mixing across chains.