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Book Review: A Handbook of Statistical Analyses using Stata, 2nd Edition
Sophia Rabe-Hesketh and Brian Everitt, Boca Raton, Fl: Chapman & Hall/CRC, 2000. 210 pp. $39.95
This book is neither a statistical textbook nor a Stata software reference manual. Rather, A
Handbook of Statistical Analyses using Stata is more of a concise Stata “how-to” manual
that takes readers through the analysis of a dozen different data sets, each requiring the
application of one or more statistical methods. It progresses from producing simple
descriptive statistics in Stata through the Stata commands for more advanced analytical
techniques such as generalized linear models, survival analysis, and maximum likelihood
In its second edition, A Handbook of Statistical Analyses using Stata is well written and
nicely organized. It is designed for readers either already familiar with the statistical
techniques it presents or for those sufficiently sophisticated to be able to learn the requisite
statistical details from other sources. Readers with solid statistical training, but unfamiliar
with Stata, will find this book to be a succinct and pleasant introduction to the software. As
the authors state in their Preface, “Our hope is that this approach will provide a useful
complement to the excellent but very extensive Stata manuals.” The second edition is an
update of the original edition from Stata 5 to Stata 6.
In the first chapter, the reader is given a concise overview (24 pages) of the Stata interface
and syntax. This chapter provides all of the fundamental commands necessary to become
immediately functional in the software. Then, each subsequent chapter presents a problem
and data set followed by a step-by-step analysis in Stata. The data sets are largely taken
from clinical trials or epidemiological studies. While each chapter does attempt to briefly
describe the particular statistical technique used, the level of detail varies and is often
relatively superficial. However, this allows the authors to get right to point – presenting
Stata in the context of real problems and real analysis.
The scope and focus of the book is best illustrated by its Table of Contents:
Chapter 1: A Brief Introduction to Stata
Chapter 2: Data Description and Simple Inference: Female Psychiatric Patients
Chapter 3: Multiple Regression: Determinants of Pollution in U.S. Cities
Chapter 4: Analysis of Variance I: Treating Hypertension
Chapter 5: Analysis of Variance II: Effectiveness of Slimming Clinics
Chapter 6: Logistic Regression: Treatment of Lung Cancer and Diagnosis of Heart Attacks
Chapter 7: Generalized Linear Models: Australian School Children
Chapter 8: Analysis of Longitudinal Data I: The Treatment of Postnatal Depression
Chapter 9: Analysis of Longitudinal Data II: Epileptic Seizures and Chemotherapy
Chapter 10: Some Epidemiology
Chapter 11: Survival Analysis: Retention of Heroin Addicts in Methadone Maintenance
Chapter 12: Principal Components Analysis: Hearing Measurement using an Audiometer
Chapter 13: Maximum Likelihood Estimation: Age of Onset of Schizophrenia
Readers interested in a further description of each chapter should consult the recent review
by Tony Lachenbruch in The American Statistician (2000). While this review was for the
first edition, the chapter descriptions are still relevant.
A Handbook of Statistical Analyses using Stata could be useful in filling specialized
pedagogical niches. While the text assumes a level of technical statistical sophistication that
makes is unsuitable for introductory or lower-level courses, it might form the basis for an
advanced undergraduate or graduate course in applied data analysis. It could be particularly
relevant in a curriculum where students must first take a number of theoretical statistical
courses, especially in schools of public health and other health-related settings, followed by
a course focused on applied data analysis. It could also be used as a supplementary text for
other courses that require the use of Stata.
Each chapter has exercises at the end. However, I found the exercises relatively simple and
limited to posing minor variants of the analysis presented within the chapter, mainly to
motivate the use of alternate Stata syntax. These exercises were sufficient in the context of
learning to use Stata. However, I suggest that expanding the exercises would improve the
text’s usefulness in the classroom. In particular, I would like to see new exercises for each
chapter based on a second data set that is not used in the chapter. This data set would be
similar in scope and analytical requirements to the one presented in the chapter, but also
sufficiently different so that students could do their own analysis (prompted by the exercise
questions) from scratch. This would allow the instructor to use the chapter data set and
analysis in a lecture and yet still have other material for student homework and exercises.
Readers should note that the book is focused on the “Intercooled” version of Stata for
Windows. Also, in the never-ending race of software manuals to keep up with the latest
software revisions, Stata 7 has recently been released, which may date some of the material
presented. However, since I do not have access to Stata 7 as of this writing, I cannot judge
how much different that version is and how much of an effect those changes will have on
this text. None-the-less, this book provides an excellent, interesting, and efficient
introduction to Stata that I can easily recommend. And, I am sure a third edition is already
in the works.
Ronald D. Fricker, Jr.
Cox, Nick. 2000. Book Review: A Handbook of Statistical Analysis using Stata.
Biometrics, 56, pp. 650-651.
Lachenbruch, Peter A. 2000. Book Review: A Handbook of Statistical Analysis using Stata.
The American Statistician, 54, pp. 153-154.