This essential handbook provides an introduction to the use of SAS for a variety of statistical analyses. Each chapter describes a particular technique applied to a particular data set, describes the relevant questions, gives a brief account of the methods used, details the SAS instructions needed to undertake analysis, and interprets the SAS output.
Handbook of Statistical Analysis Using SAS serves as an easy introduction to using SAS for statistics and as a stepping stone to using the more comprehensive SAS manuals available. Statistical users of SAS, especially in the pharmaceutical industry and medical research, will find this book of particular interest.
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Geoff Der works as a consulting statistician at the Medical Research Council Social and Public Health Sciences Unit in Glasgow, Scotland. His current research interests include the relationship between cognitive functioning and health, income and health, and models for longitudinal data.
In 2005, Brian S. Everitt retired from being head of the Department of Biostatistics and Computing in the Institute of Psychiatry at King’s College London, UK. Currently working on his 60th statistics book, he acts as a statistical consultant to a number of companies.
... a concise but simple manual for using SAS. It has put thousands of pages of SAS manuals in less than 400 pages of a paperback...describes the use of SAS Version 8.1 in the Microsoft Windows Environment. However, the programming part can be used in almost any environment ... The authors have again done an excellent job of explaining each statement as well as the resulting output ... In summary, the handbook introduces SAS programming through a number of datasets of varied complexity, makes the datasets suitable for analysis through programming statements, then uses SAS procedures for analysis. SAS procedures and the resulting outputs are properly explained, and suggestions for appropriate analyses are provided where necessary. Overall, I consider this an excellent handbook for a beginning SAS user. Statisticians and nonstatisticians can both benefit from this book.
-The American Statistician, November 2002
The aim of the book - to provide an easy to read reference for new users of SAS without having to resort to trawling through the manuals -- is well met. I feel that this would be a very good starting point for any student or researcher who wishes to learn the basics about the statistical techniques covered and how they can be programmed in SAS. The examples provided in the book cover a good range of data situations and analysis techniques.
-M. K. Smith, Biometrics, June 2002
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