I'm trying to learn more about survival analysis and I could really use some suggestions for good texts on the topic. I have a fairly strong background in applied statistical analyses (quantitative psychology specifically), but survival analysis is a bit of a weak spot for me. Ideally I'm looking for a text that covers the topic with a good deal of depth (and particularly covers issues of interval censoring/left censoring), but isn't overly technical (e.g., Casella and Berger type texts would be "overly technical").

A graduate level text along the lines of "Statistical Rethinking" in terms of complexity and depth would be perfect. Applied examples certainly do not need to be psychological. It would be fantastic if the book used R, but again, not necessary. All that said, any suggestions would be appreciated.


I would suggest:

Kleinbaum, David G. and Mitchel Klein (2010), Survival Analysis: A Self-Learning Text. Springer

(which is quite easily readable and not "overly technical"). And then:

Moore, Dick (2016), Applied Survival Analysis Using R. Springer.

which is a little more mathematically heavy but provides good references on R packages.

  • 1
    $\begingroup$ +1 Kleinbaum and Klein, a great self-learning text for folks around an MPH level understanding of biostat. $\endgroup$
    – AdamO
    Jul 13 '21 at 22:37
  • $\begingroup$ Thanks for the suggestions, I'll be sure to check those out. $\endgroup$
    – pgok
    Jul 14 '21 at 16:08

Applied Survival Analysis, Regression Modeling of Time-to-Event Data - Hosmer Lemeshow May

Covers important topics like recurrent event analyses, interval censoring, frailty, time varying covariates, etc. Has only a few displays with calculus, no proofs, concepts and applications. Plus, Norm Breslow used this text in his survival analysis.


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