Bücher veröffentlicht von SAS Institute

Find guidance on using SAS for multiple imputation and solving common missing data issues. Multiple Imputation of Missing Data Using SAS provides both theoretical background and constructive solutions for those working with incomplete data sets in an engaging example-driven format. It offers practical instruction on the use of SAS for multiple imputation and provides numerous examples that use a variety of public release data sets with applications to survey data. Written for users with an intermediate background in SAS programming and statistics, this book is an excellent resource for anyone seeking guidance on multiple imputation. The authors cover the MI and MIANALYZE procedures in detail, along with other procedures used for analysis of complete data sets. They guide analysts through the multiple imputation process, including evaluation of missing data patterns, choice of an imputation method, execution of the process, and interpretation of results. Topics discussed include how to deal with missing data problems in a statistically appropriate manner, how to intelligently select an imputation method, how to incorporate the uncertainty introduced by the imputation process, and how to incorporate the complex sample design (if appropriate) through use of the SAS SURVEY procedures. Discover the theoretical background and see extensive applications of the multiple imputation process in action. This book is part of the SAS Press program.

SAS Programming with Medicare Administrative Data is the most comprehensive resource available for using Medicare data with SAS. This book teaches you how to access Medicare data and, more importantly, how to apply this data to your research. Knowing how to use Medicare data to answer common research and business questions is a critical skill for many SAS users. Due to its complexity, Medicare data requires specific programming knowledge in order to be applied accurately. Programmers need to understand the Medicare program in order to interpret and utilize its data. With this book, you'll learn the entire process of programming with Medicare datafrom obtaining access to data; to measuring cost, utilization, and quality; to overcoming common challenges. Each chapter includes exercises that challenge you to apply concepts to real-world programming tasks. SAS Programming with Medicare Administrative Data offers beginners a programming project template to follow from beginning to end. It also includes more complex questions and discussions that are appropriate for advanced users. Matthew Gillingham has created a book that is both a foundation for programmers new to Medicare data and a comprehensive reference for experienced programmers. This book is part of the SAS Press program.

Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners. As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software. This book is part of the SAS Press program.