Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudinal and survival data analysis, missing data, generalized additive models (GAMs), and Bayesian methods. The book focuses on performing these analyses using SAS, the software package of choice for those analysing medical data.
- Covers the planning stage of medical studies in detail; several chapters contain details of sample size estimation
- Illustrates methods of randomisation that might be employed for clinical trials
- Covers topics that have become of great importance in the 21st century, including Bayesian methods and multiple imputation
Its breadth and depth, coupled with the inclusion of all the SAS code, make this book ideal for practitioners as well as for a graduate class in biostatistics or public health.
Complete data sets, all the SAS code, and complete outputs can be found on an associated website: http://support.sas.com/amsus
Table of Contents
An Introduction to SAS. Statistics and Measurement in Medicine. Clinical Trials. Epidemiology. Meta-analysis. Analysis of Variance and Covariance. Scatter Plots, Correlation, Simple Regression, and Smoothing. Multiple Linear Regression. Logistic Regression. The Generalised Linear Model. Generalised Additive Models. The Analysis of Longitudinal Data I. The Analysis of Longitudinal Data II: Linear Mixed-Effects Models for Normal Response Variables. The Analysis of Longitudinal Data III: Non-Normal Responses. Survival Analysis. Cox’s Proportional Hazards Models for Survival Data. Bayesian Methods. Missing Values.
"Each chapter in the book is well laid out, contains examples with SAS code, and ends with a concise summary. The chapters in the book contain the right level of information to use SAS to apply different statistical methods. … a good overview of how to apply in SAS 9.3 the many possible statistical analysis methods."
—Caroline Kennedy, Takeda Development Centre Europe Ltd., Statistical Methods for Medical Research, 2015
"… a well-organized and thorough exploration of broad coverage in medical statistics. The book is an excellent reference of statistical methods with examples of medical data and SAS codes for statisticians or statistical analysts who are working in the medical/clinical area. It also can be a reference book for an introductory or intermediate graduate biostatistics course."
—Jun Zhao, Journal of Biopharmaceutical Statistics, 24, 2014
"A recent request to a statistical professional body by a doctor seeking help with analysing data they had collected was greeted with derision by some of the members of that body. … The doctor in question may have been better served by simply purchasing this wide-ranging and accessible book. Medical students would also appreciate the range of topics addressed. … I think consultant statisticians would also appreciate the refreshers/introductions to statistical techniques and the SAS code for each. Indeed SAS code is liberally scattered throughout the text, and a couple of SAS macros are referred to in the meta-analysis chapter. … The text is supported by ten pages of references and a sizeable index. The code and example data sets can be downloaded from the SAS website."
—Alice Richardson, International Statistical Review (2013), 81
"Applied Medical Statistics Using SAS is a thorough documentation of statistical methods, inclusive of medical data sets and SAS code. The book would make an excellent reference guide for medical data analysts with access to base SAS 9.3 or a textbook for an introductory and intermediate graduate biostatistics course. … [It] comes to the market at an appropriate time in the extension of statistical applications to the medical industry … The thoroughness of procedures and the consideration the authors included in the selection of graphs, SAS code, and theory allow this book to be a resourceful companion for medical analysts. If looking for a broad selection of medical analyses using base SAS 9.3, this is the book for you; in addition, if a particular topic is required for further analyses, the book references additional sources."
—Journal of Statistical Software, Volume 52, January 2013