Good and Great Statistics and Epidemiology Books

These are my favorite statistics and technical books, in no particular order.  My biases are:

1. I want well written prose instead of careful derivations
2. I dislike textbooks that do not include programming examples
3. I passionately dislike textbooks that have problems without answers (HEY PUBLISHERS, STUDENTS KNOW ABOUT GOOGLE.  DO YOU?)
4. I use Microsoft Windows
5. I program primarily in SAS

If you have a favorite that I should read let me know ( )

General Statistics and Epidemiology

How to Lie with Statistics by Huff

• The closest thing to a Platonic perfect first text in statistics
• A supplement to go with a "real" textbook in first quarter of undergraduate statistics
• Almost no math
• No programming

Statistics (3^rd edition) by Freedman et al

• This is the best “real” statistics book I have read.
• It will help you develop intuitions about how common statistics really work.
• It needs a programming supplement.
• I don’t know about the fourth edition yet

Epidemiology: Study Design and Data Analyses (1^st or 2^nd edition) by Woodward

• Easily the best practical book on Epidemiology but the price is prohibitive.
• It includes SAS examples for Epidemiology and Biostatistics.

Biostatistics: The Bare Essentials (2^nd or 3^rd edition) by Norman & Streiner

• My favorite biostatistics book despite having no programming (hint hint it must be darn good)
• It has excellent breadth for epidemiology and biostatistics.
• Irreverent style and wonderful writing
• For better or worse, very little math

Applied Longitudinal Data Analysis by Singer and Willett

• The first book you want to read on longitudinal/repeated measures/mixed models/ hierarchical linear models
• The best writing you will ever find in any text book.
• Code for all major statistics packages
• Hands down my all time favorite statistics book.

Regression Modeling Strategies by Harrell

• A fantastic second book on regression.
• It covers how to pick variables for predicting outcomes far better than any other book I have seen.
• It is written for S-Plus users but is very useful for everybody.

An Introduction to Categorical Data (1^st or 2^nd edition) Analysis by Agresti

• This is the second book you want to read on categorical data analysis.
• It is excellent but not for amateurs.
• SAS but the code is antiquated

Survival Analysis : A Self-Learning Text (1^st edition) by Kleinbaum

• An excellent introduction which is more theoretical than the Allison SAS based book
• Does a great job separating the math from the concepts
• Some but nowhere enough programming examples
• First edition is better than the second.

Applied Logistic Regression by Hosmer & Lemeshow

• Perhaps a good first book definitely a great second book on the topic
• Excellent theoretical coverage
• Some SAS programming examples

Statistical Methods for Rates and Proportions by Fleiss, Levin & Paik

• The best written in-depth coverage of the topics
• I have written SAS to go with much of the book

Bayesian Statistical Inference by Iversen

• A tiny but wonderfully written introduction to the concepts
• Not much math and no code

SAS beyond HRP 223

Common Statistical Methods for Clinical Research with SAS Examples (2nd Edition) by Walker

• The first edition was a cookbook which clearly said how to do common statistics.
• The second edition has more examples and more explanations of what is going on in the statistics.
• I highly recommend it if you have a statistics course that is too theoretical.

Survival Analysis using the SAS System by Allison

• an awesome applied survival book
• it needs a second edition

Logistic Regression Using the SAS System by Allison

• a very good applied logistic regression book
• it needs a second edition

Categorical Data Analysis Using the SAS System (2nd edition) by Stokes et al

• This is the bible for doing categorical analyses in SAS.
• While not bad, it does not read easily.

R

Data Manipulation with R by Spector

• The name says it all.
• This should be the first book people read on R.
• It covers the stuff you need to know before you can graph and analyze.

Introductory Statistics with R by Dalgard

• If you need to learn R start with Spector and use this also.

Data Analysis and graphics using R by Maindonald and Braun

• Fantastic coverage of the graphics you should be doing with all the main analyses out there.

Using R for Introductory Statistics by Verzani

• I love this book for the general breadth of coverage.
• Everything is clearly presented.
• This would be my recommendation on where to start in R except that the index is the worst in the history of publishing. I frequently find myself thinking, “I know the answer is in Verzani” but then I can’t find it.

Math

Matrix Algebra as a Tool by Hadi

• A great book to use to learn matrix math.
• Needs a SAS/IML programming supplement

Matrix Albegra An Introduction by Namboodiri

• Nicely written but a bit too much instruction on doing things by hand
• Has a bit of SAS code

Statistical Graphics

Creating More Effective Graphs by Robbins

• This should be required reading for anyone who produces any graphics. Just get it.
• It is full of dos and don’ts for scientific graphics.
• About 400 pages with pairs of pages showing a graphic and discussion.

The Visual Display of Quantitative Information by Tufte

• All of Tufte's books are wonderful to look at and read.  This one is the most technical of the bunch but it is still not scientifically rigorous for my taste.
• This book belongs on a coffee table rather than a bookshelf.

Visualizing Data and also The Elements of Graphing Data by Cleveland

• Simply brilliant if you want to learn how to represent data graphically and think about the psych behind what makes a good graphic.
• Lots of S-Plus examples

Graphic Discovery by Wainer

• Great discussion of what makes a good graphic good
• History of scientific graphics
• Famous graphics and why they do and don’t work

Statistics with S-Plus

An Introduction to S and S-Plus by Spector

• A much better introduction than the commonly suggested Venables and Ripley books.
• Clearly written, short and to the point.

Perl

Learning Perl by Schwartz and Christiansen

• Focuses on UNIX Perl but it is much better than the windows equivalent book.

SAMS Teach Yourself Perl in 21 Days by Demay

• Almost every topic I have needed is in here.

SQL

The Practicle SQL handbook by Bowman, Emerson and Darnovsky

• Great general SQL book

Proc SQL by Example Using SQL within SAS

• Good book covers basic to advanced stuff

Proc SQL – A Primer for SAS Programmers www2.sas.com/proceedings/sugi31/250-31.pdf

• A great little PDF comparing SQL and data step code