A Tutorial of Survival Modeling to Capture Covariate Effect

Abstract

Mixture modeling in general and expectation–maximization in particular are too cumbersome and confusing for applied health researchers. Consequently, the full potential of mixture modeling is not realized. To remedy the deficiency, this tutorial article is prepared. This article addresses important applied problems in survival analysis and handles them in deeper generality than the existing work, especially from the point of view of taking covariates into account. In specific, the article demonstrates the concepts, tools, and inferencial procedure of mixture modeling using head-and-neck cancer data and survival time after heart transplant surgery data.

Keywords:

• Accelerated failure time
• BIC
• EM algorithm
• Information matrix
• Parametric mixture.

Mathematics Subject Classification:

• 60E05
• 62-07
• 62F03
• 62P10

Acknowledgments

The authors appreciate and thank the editor and the referees for helpful suggestions. After incorporating their suggestions, this revised version reads better.