Synopses & Reviews
Updated to reflect SAS 9.2, A Handbook of Statistical Analyses using SAS, Third Edition continues to provide a straightforward description of how to conduct various statistical analyses using SAS.
Each chapter shows how to use SAS for a particular type of analysis. The authors cover inference, analysis of variance, regression, generalized linear models, longitudinal data, survival analysis, principal components analysis, factor analysis, cluster analysis, discriminant function analysis, and correspondence analysis. They demonstrate the analyses through real-world examples, including methadone maintenance treatment, the relation of cirrhosis deaths to alcohol consumption, a sociological study of children, heart transplant treatment, and crime rate determinants.
With the data sets and SAS code available online, this book remains the go-to resource for learning how to use SAS for many kinds of statistical analysis. It serves as a stepping stone to the wider resources available to SAS users.
About the Authors
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 Kinga (TM)s College London, UK. Currently working on his 60th statistics book, he acts as a statistical consultant to a number of companies.
Synopsis
Presenting an accessible and comprehensive introduction to statistical analysis, the third edition of A Handbook of Statistical Analyses using SAS has been updated to reflect the latest SAS version 9.2, with all new syntax included. This edition of a bestseller also features two entirely new chapters, one of which addresses the topic of generalized additive models. Expanding on the already large number of detailed worked examples offered in the previous editions, this book presents additional exercises, selected solutions contained in an appendix, and a full solutions manual. All datasets and SAS code are available for download on the web.
Synopsis
Updated to reflect SAS 9.2, this new edition continues to provide a straightforward description of how to conduct various statistical analyses using SAS. Each chapter shows how to use SAS for a particular type of analysis.
Synopsis
Updated to reflect SAS 9.2, A Handbook of Statistical Analyses using SAS, Third Edition continues to provide a straightforward description of how to conduct various statistical analyses using SAS.
Each chapter shows how to use SAS for a particular type of analysis. The authors cover inference, analysis of variance, regression, generalized linear models, longitudinal data, survival analysis, principal components analysis, factor analysis, cluster analysis, discriminant function analysis, and correspondence analysis. They demonstrate the analyses through real-world examples, including methadone maintenance treatment, the relation of cirrhosis deaths to alcohol consumption, a sociological study of children, heart transplant treatment, and crime rate determinants.
With the data sets and SAS code available online, this book remains the go-to resource for learning how to use SAS for many kinds of statistical analysis. It serves as a stepping stone to the wider resources available to SAS users.