Using SAS for Data Management, Statistical Analysis, and Graphics

ISBN-13: 9781138469846 / Angielski / Twarda / 2017

Ken Kleinman

Opis

Suitable for statistical coders, this book presents an easy way to learn how to perform an analytical task in SAS, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation.

Recenzje

This book is a well-organized reference text that summarizes and illustrates SAS code and common SAS features most often used by statistical analysts and others engaged in research and data analysis. … a handy reference tool for common tasks performed in SAS due to the book’s task-oriented nature and the broad range of topics covered. This book would also nicely serve as a supplemental reference text for an introductory SAS programming class.
—Journal of Biopharmaceutical Statistics, Issue 3, 2011

Spis treści

Introduction to SAS. Data Management. Common Statistical Procedures. Linear Regression and ANOVA. Regression Generalizations. Graphics. Advanced Applications. Appendix. Bibliography. Indices.

O autorze

Ken Kleinman is an associate professor in the Department of Population Medicine at Harvard Medical School in Boston, Massachusetts. His research deals with clustered data analysis, surveillance, and epidemiological applications in projects ranging from vaccine and bioterrorism surveillance to observational epidemiology to individual-, practice-, and community-randomized interventions. Nicholas J. Horton is an associate professor in the Department of Mathematics and Statistics at Smith College in Northampton, Massachusetts. His research interests include longitudinal regression models and missing data methods, with applications in psychiatric epidemiology and substance abuse research.