Statistical Modeling for Biomedical Researchers: A Simple Introduction to the Analysis of Complex Data (Cambridge Medicine),   ISBN:9780521614801

Customer Rating: 

This text is especially valuable because it is written in clear and concise language. It thus serves the needs of the biostatistical community while remaining accessible to the non-biostatistician. The latter is what is so often lacking in textbooks in this discipline. The new 2009 edition builds on and adds to the strengths of the first. As a clinical investigator, I turn to this first when I have a complex data issue that I need clarification about.

Customer Rating: 

This is a highly recommended book if you are trying to use Stata in biomedical research. This covers most of the standard procedures (t-tests, linear regression, multiple comparisons, logistic and other contingency table methods, Cox PH, Poisson (log-linear), GEE) and a reasonable amount of noncalculus statistical formula derivation to show what goes on inside the box. ANOVA is relegated to the back of the book, because in the author's opinion, the amount of control needed to pull off these studies is not normally feasible and GLM can cover the same ground. There isn't any other book that addresses GEE as comprehensively as this book. The Vittinghoff book is also recommended as a companion piece to give a more in-depth approach to regression topics.

Customer Rating: 

If you are working with Stata this book will be a good help to understand the basic concepts of the multivarite analysis.

Customer Rating: 

Dupont's "Statistical Modeling for Biomedical Researchers" is an accessible, straightforward, easy-to-read text for students and/or researchers w/ some elementary background in biostatistics. As previous reviewers have indicated, this is largely a problem-based text, so for those of you who seek a detailed theoretical explanation of the tools presented therein, you may want to look elsewhere. A major advantage, however, is Dupont's presentation of how to run the respective analyses using the statistical software package, Stata, although it should be noted that the syntax presented is for version 7 of Stata -- not version 8. Parenthetically, all of the code -- w/ the exception of the graphing commands -- are essentially the same between versions. In short, this text is a good introduction to some of the techniques typically not discussed in an elementary biostatistics course, although the book is best characterized as an invaluable adjunct to more theoretical, comprehensive biostatistics textbooks.

Customer Rating: 

I used this book as the text for a biostatistics class that used STATA as the statistitical package. I found the organization, problems, and the STATA output the book provides, all very helpful. In addition, as I moved systematically through the book, the tips regarding using the STATA features were key to my learning many of the practical aspects of the STATA program.