Longitudinal Data and SAS: A Programmer's Guide (Paperback)

by Ronald P. Cody (Author) "Suppose you have a SAS data set of clinical data..." (more)
Key Phrases: small test data, other grouping variable, macro variable containing, Guide Program, Study One, Computing Differences (more...)

Editorial Reviews

Review
Longitudinal Data and SAS: A Programmer's Guide, by Ron Cody, is a comprehensive look at the techniques to deal with longitudinal data - data that spans multiple observations. Ron's book looks at the problems encountered when working with longitudinal data, or in restructuring data into longitudinal data, and then examines techniques to solve each problem in detail. Some are very simple techniques, some are very novel techniques. Each is a useful addition to the basic knowledge that every SAS user should possess. --S. David Riba, JADE Tech, Inc., Corporate Actuarial Planning Unit, The Hartford

Ron Cody has done it again. His newest Book by Users Press titled Longitudinal Data and SAS: A Programmer's Guide, offers new and intermediate users, working with longitudinal data, the basic tools for success. If you wish to learn by example, this book provides short SAS programs covering the most often used techniques for summarizing and restructuring longitudinal data. The comments following each program provide important hints to remember. You will gain experience by testing methods, and verifying results. --Karol Katz M.S., Programmer/Analyst , Yale University School of Medicine

This book is a comprehensive look at techniques to deal with longitudinal data, examining detailed methods to solve each problem. -- S. David Riba JADE Tech, Inc., Corporate Actuarial Planning Unit, The Hartford

This book offers programmers the basic tools for success. It provides examples and experience through testing methods and verifying results. -- Karol Katz M.S., Programmer/Analyst, Yale University School of Medicine

Product Description
Working with longitudinal data introduces a unique set of challenges. Once you've mastered the art of performing calculations within a single observation of a data set, you're faced with the task of performing calculations or making comparisons between observations. It is simple to look backward in data sets, but how do you look forward and across observations? Ron Cody provides straightforward answers to these and other questions. This book details useful techniques for conducting operations between observations in a SAS data set. For quick reference, the book is conveniently organized to cover: tools--an introduction to powerful SAS programming techniques for longitudinal data; case studies--a variety of illuminating examples that use Ron's techniques; and macros--detailed descriptions of helpful longitudinal data macros. Beginning to intermediate SAS users will appreciate this book's informative, easy-to-comprehend style. And those users who frequently process longitudinal data will learn to make the most of their analyses by following Ron's methodologies.

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Product Details

• Paperback: 150 pages
• Publisher: SAS Publishing; 1 edition (October 15, 2001)
• Language: English
• ISBN-10: 1580259243
• ISBN-13: 978-1580259248
• Product Dimensions: 8.9 x 7.5 x 0.4 inches
• Shipping Weight: 12 ounces (View shipping rates and policies)
• Average Customer Review: 3.7 out of 5 stars See all reviews (3 customer reviews)
• Amazon.com Sales Rank: #533,009 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

37 of 38 people found the following review helpful:

4.0 out of 5 stars thumbs up from me, May 30, 2008

By	Michael R. Chernick "statman31147" (Holland PA) - See all my reviews (REAL NAME)

I have to give a very positive review to this book. Cody writes very nice introductory applied statistics books that emphasize SAS applications. This has good illustrations of a very important type of data analysis that biostatisticians doing clinical research need to know. Also, because in the analysis of clinical trials the FDA prefers analysis to be done using SAS, applications in SAS are important to have. If some or even most of this material is covered in another text as one reviewer suggests that does not mean that the biostatistician might not prefer to select this text which concentrates solely on longitudinal data. Also in the pharmaceutical industry where many clinical trials are conducted on longitudinal data, SAS programmers who are not statisticians are employed and books like this one can be of great use to them in their careers. The correct use of PROC Mixed in the analysis of longitudinal data is tricky and mistakes are easy to make.

6 of 6 people found the following review helpful:

2.0 out of 5 stars Disappointed, March 28, 2008

By	Yin Luo (New York, US) - See all my reviews (REAL NAME)

This book is clearly written, but it's mostly a subsection of another book by the same author, Applied Statistics and the SAS Programming Language. There are a couple of case studies that are not included in the other book, but I don't know if that will be worth the price.

Overall, the coverage is superficial. Managing longitudinal data involves heavy time series cross sectional analysis, but the author almost ignored time series data management completely. SAS is pretty weak in time series analysis and this book did not help much either.

2 of 2 people found the following review helpful:

5.0 out of 5 stars Worth every penny!, February 26, 2008

By	M&M Catboy (Chicago, Illinois, USA) - See all my reviews

This book has helped me so much at work. I like the clear explanation of what each line in the programs. Good examples of each topic.