Thomas Lumley

English

Research Papers in Economics

JSS Journal of Statistical Software
March 2005, Volume 12, Book Review 1. http://www.jstatsoft.org/
Reviewer: Thomas Lumley
University of Washington
An Introduction to Survival Analysis using Stata (Revised Edition)
Mario A. Cleves, William W. Gould, Roberto G. Gutierrez
Stata Press, College Station, TX, 2004.
ISBN 1-881228-84-3. 308 pp. $52.00 (P).
The authors note in the Preface to this book that“[it] grew out of software, but nonetheless,
it is not a manual”. An Introduction to Survival Analysis using Stata is certainly focused on
the Stata implementation of survival analysis. It is published by the publishers of Stata, and
written by the authors of the Stata survival analysis commands. There are many advantages
in having data analysis methodology presented with concrete examples, by people who un-
derstand what computations are going on. There are also risks: the temptation to ignore or
sidestep infelicities in implementation, and to overemphasize computational points that are of
no importance to the typical user. Fortunately, the Stata implementation of survival analysis
is well thought out, and a description of what Stata can do is a reasonable introduction to
the ﬁeld of survival analysis.
The book assumes some familiarity with Stata and with statistics. Epidemiologists with a
background in logistic regression modeling would be one example of a suitable audience. It
begins by describing hazard and cumulative hazard, truncation and censoring. This leads to
a discussion of the possibility of diﬀerent time scales for a survival analysis, and the manifold
options for specifying survival data structures in the -stset- command. While covering all
this material in one place saves space, it is perhaps a little confusing for someone without
survival analysis experience — a course in survival analysis would usually start with simple
right censoring and defer all the complications for a few weeks. After discussing one- and
two-sample summaries and tests the book moves on to the Cox model, where it covers ﬁtting,
time-varying covariates, and shared frailty models. The ﬁnal chapters cover similar topics for
parametric proportional hazards and accelerated failure models.
The explanations of statistical methods and issues in the book are usually good. There are
a few things I would quibble with, such as the characterization of marginal hazard ratios as
‘biased’ in the presence of correlation — an issue that some of these same authors have handled
more carefully in discussions of longitudinal data analysis. Perhaps the most signiﬁcant
complaint is that the term ‘at risk’ is used for times at which a person might have had an
event, but when such an event would not have been observed, and the term ‘under observation’
is used for times when an event would have been observed. In both epidemiology and the2 An Introduction to Survival Analysis using Stata (Revised Edition)
mathematical parts of survival analysis the term ‘at risk’ is more often used to mean ‘able to
have an event observed’. The authors’ terminology is arguably more logical, but as they note
in their introduction “if we are going to communicate by the written word, we have to agree
on what these terms mean.”
An obvious comparison of this book is to ?, whose ﬁrst author wrote the very similar survival
analysis implementation in S-PLUS and R. The book of ? is tied less tightly to the imple-
mentation, and covers rather more of the statistical theory. Perhaps a fair summary of the
diﬀerence is that ? have written the sort of book that would be appreciated by people who
use S, and Cleves et al. have written for the sort of audience that uses Stata.
References
Therneau TM, Grambsch PM (2000). Modelling Survival Data: Extending the Cox Model.
Springer, New York.
Reviewer:
Thomas Lumley
University of Washington
Department of Biostatistics
Box 357232
Seattle, WA 98195-7232, United States of America
E-mail: tlumley@u.washington.edu
Journal of Statistical Software Published: 2005-03-09
March 2005, Volume 12, Book Review 1.
http://www.jstatsoft.org/

An Introduction to Survival Analysis using Stata

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Research Papers in Economics