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Longitudinal Data and SAS: A Programmer's Guide
 
 
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Longitudinal Data and SAS: A Programmer's Guide [Paperback]

Ronald P. Cody (Author)
3.7 out of 5 stars  See all reviews (3 customer reviews)

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Book Description

October 15, 2001 1580259243 978-1580259248 1
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's easy 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. Longitudinal Data and SAS 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 users who frequently process longitudinal data will learn to make the most of their analyses by following Ron's methodologies.

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Editorial Reviews

Review

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

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

About the Author

By day, Ron Cody, Ed.D. is a professor and researcher at the Robert Wood Johnson Medical School. With more than 20 years of experience using, teaching, and writing about SAS, he has undeniably earned his "SAS expert" title.

Ron applies his expertise in this latest addition to his impressive list of works, including The SAS Workbook The SAS Workbook Solutions Cody's Data Cleaning Techniques Using SAS Software as well as his coauthored books SAS Programming by Example Applied Statistics and the SAS Programming Language, Fourth Edition.


Product Details

  • Paperback: 150 pages
  • Publisher: SAS Publishing; 1 edition (October 15, 2001)
  • Language: English
  • ISBN-10: 1580259243
  • ISBN-13: 978-1580259248
  • Product Dimensions: 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 Best Sellers Rank: #546,574 in Books (See Top 100 in Books)

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40 of 41 people found the following review helpful:
4.0 out of 5 stars thumbs up from me, May 30, 2008
This review is from: Longitudinal Data and SAS: A Programmer's Guide (Paperback)
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.
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9 of 9 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)   
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This review is from: Longitudinal Data and SAS: A Programmer's Guide (Paperback)
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.
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2 of 2 people found the following review helpful:
5.0 out of 5 stars Worth every penny!, February 26, 2008
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This review is from: Longitudinal Data and SAS: A Programmer's Guide (Paperback)
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.
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Inside This Book (learn more)
First Sentence:
Suppose you have a SAS data set of clinical data. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
small test data, other grouping variable, macro variable containing, last visit for each patient, nonmissing values, retained variables, book frequencies, clinical database, data set name, diagnosis code, useful macros, flag variable, temporary variables, longitudinal data, only one visit, procedure option, multiple observations
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Guide Program, Study One, Computing Differences, Summarizing Data Using, Heart Problem, Selecting All Patients, Useful Macros, Ascertain Vitamin Use, Macro Name, Producing Summary Reports, Study Three, Study Two, Education Adult, Subset of Subjects
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