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A Tutorial of Survival Modeling to Capture Covariate Effect

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  • Ying Zhang
  • Jagbir Singh
  • Ramalingam Shanmugam

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.

Suggested Citation

  • Ying Zhang & Jagbir Singh & Ramalingam Shanmugam, 2015. "A Tutorial of Survival Modeling to Capture Covariate Effect," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(13), pages 2788-2797, July.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:13:p:2788-2797
    DOI: 10.1080/03610926.2013.783070
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