Learn how to work smart in planning and conducting research projects with this new resource for successful research data management (RDM). You can read about basic concepts and techniques of RDM and then see them illustrated in case studies from a variety of research fields. Readers with some experience leading research projects and an understanding of programming basics will value both the theoretical and the practical information provided here. In addition to RDM methodology and four case studies, the book features a concise list of tips to remember at the end of each concepts chapter, an appendix with SAS programming tips, and a list of recommended supplemental texts, including SAS manuals and SUGI papers. Ideal for researchers in the field and the classroom.

Supports releases 6.09 and higher of SAS software.

About the Author

J. Meimei Ma, Ph.D.

J. Meimei Ma, Ph.D., has over 17 years experience using SAS software

for statistical research programming, especially for categorical and

descriptive analysis of data. Ma's current activities include

programming for clinical trials projects with special interest in

large integrated databases and database documentation for the

pharmaceutical industry. Ma has been widely published and has

presented papers at SUGI.

William S. Calvert

William S. Calvert directs a drug safety monitoring program at

a government agency. Formerly, he provided contract research

services to the pharmaceutical, health care, and insurance

industries. Calvert's background includes a broad range of

publications, SUGI presentations, and several years of

providing computing support at the National Institutes of Health.

He has over 16 years experience using SAS software with emphasis

on research data management, data analysis, and statistical

computing and design.

"About this title" may belong to another edition of this title.

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