Statistical analysis is ubiquitous in modern medical research. Logistic regression, generalized linear models, random effects models, and Cox's regression all have become commonplace in the medical literature. But while statistical software such as SAS make routine application of these techniques possible, users who are not primarily statisticians must take care to correctly implement the various procedures and correctly interpret the output.
Statistical Analysis of Medical Data Using SAS demonstrates how to use SAS to analyze medical data. Each chapter addresses a particular analysis method. The authors briefly describe each procedure, but focus on its SAS implementation and properly interpreting the output. The carefully designed presentation relegates the theoretical details to "Displays," so that the code and results can be explored without interruption. All of the code and data sets used in the book are available for download from either the SAS Web site or www.crcpress.com.
Der and Everitt, authors of the best-selling Handbook of Statistical Analyses Using SAS, bring all of their considerable talent and experience to bear in this book. Step-by-step instructions, lucid explanations and clear examples combine to form an outstanding, self-contained guide--suitable for medical researchers and statisticians alike--to using SAS to analyze medical data.
An Introduction to SAS
Describing and Summarizing Data
Scatterplots Correlation: Simple Regression and Smoothing
Analysis of Variance and Covariance
The Generalized Linear Model
Generalized Additive Models
Nonlinear Regression Models
The Analysis of Longitudinal Data I
The Analysis of Longitudinal Data II: Models for Normal Response Variables
The Analysis of Longitudinal Data III: Non-Normal Response
Analysis Multivariate Date: Principal Components and Cluster Analysis
"This is a handy book that can serve the everyday purposes of statisticians and programmers working in the pharmaceutical industry. …The book has a reasonable coverage of statistical methods that are most commonly encountered in pharmaceutical settings. … All statistical methods are explained via examples with medical background. This will help readers learn when, why, and how a specific statistical method should and could be used in certain settings, and how to implement any particular statistical method in SAS. SAS code associated with each example is provided and the corresponding output is interpreted from both statistical and clinical standpoints. … I would recommend the book as one of the desktop dictionaries for statisticians or SAS programmers who deal with medical data on a daily basis, or as an introductory book for people who wish to gain some fundamental medical statistical techniques or SAS programming. …"
—Xiaolei Li (GlaxoSmithKline), Pharmaceutical Statistics, 2008
"This monograph introduces basic statistical methods and applications to medical data using SAS software. Each chapter is accompanied by a short description of methodology, detailed explanation of SAS program code for analysis of a real medical data set, and proper interpretation of SAS output. …"
—Zentralblatt MATH, 1088
|Datasets and SAS programs.txt||Cross Platform||February 14, 2006||Contains datasets and SAS programs for all the examples in the book.|