SAS for Monte Carlo Studies: A Guide for Quantitative Researchers

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9781590471418: SAS for Monte Carlo Studies: A Guide for Quantitative Researchers
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With the advance of computing technology, Monte Carlo simulation research has become increasingly popular among quantitative researchers in a variety of disciplines. More and more, statistical methods are being subjected to rigorous empirical scrutiny in the form of statistical simulation so that their limitations and strengths can be understood. With the combination of powerful built-in statistical procedures and versatile programming capabilities, SAS is ideal for conducting Monte Carlo simulation research! Xitao Fan, Akos Felsovalyi, Stephen Sivo, and Sean Keenan's SAS for Monte Carlo Studies: A Guide for Quantitative Researchers provides detailed and practical guidance for conducting Monte Carlo studies using SAS. Quantitative researchers will find this book attractive for its practicality and for its many hands-on application examples of Monte Carlo research.

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About the Author:

Xitao Fan, Ph.D., is an Associate Professor at the Curry School of Education, University of Virginia. He specializes in educational/psychological measurement and quantitative research methods in social and behavioral sciences. He has been a SAS user for more than ten years and has used SAS in his Monte Carlo simulation studies on many occasions.

Akos Felsovalyi, M.S., is a vice president of Risk Architecture at Citigroup. He has been an avid SAS user since 1982, using the SAS System in direct marketing research and currently in Risk Management, where he applies Monte Carlo simulation to various projects.

Stephen A. Sivo, Ph.D., is a Research Psychologist and an Assistant Professor of Educational Research at the University of Central Florida. He received his Ph.D. in Research, Measurement, and Statistics from the Educational Psychology department at Texas A&M University. The primary focus of his research has centered on the use of structural equation modeling to fit time series models to longitudinal data. He has used SAS software since 1991.

Sean C. Keenan, Ph.D., is currently a vice president in Citigroup's Risk Architecture Group, where he is involved in the development of quantitative tools and methodologies for assessing credit risk for obligors and pools of obligors, as well as for a variety of credit and structured credit portfolios. His research involves a wide range of Monte Carlo applications, often with large data sets, and SAS is his preferred tool for handling these tasks. Sean holds a Ph.D. in Economics from New York University.

Review:

Although accessible to a wide range of SAS users, even experienced users will learn clever new tricks for data generation, management and analysis. This is a wonderful resource for anyone considering the use of Monte Carlo simulation methodology in SAS. --Patrick J. Curran, Ph.D., University of North Carolina at Chapel Hill

This book provides an excellent introduction to using the SAS System to conduct Monte Carlo simulation studies in a variety of substantive areas. Although the book is written at a fairly basic level, it skillfully previews many of the underlying statistical theories necessary for understanding the techniques discussed. --George A. Marcoulides, Ph.D., Editor, Structural Equation Modeling Journal

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