Applied Regression Analysis and Other Multivariable Methods

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Cengage Learning, Apr 23, 2007 - Mathematics - 928 pages
2 Reviews
This bestseller is known for its modern, practical approach to regression-analysis methods that students will find applicable to real-life problems. APPLIED REGRESSION ANALYSIS AND MULTIVARIABLE METHODS highlights the role of the computer in contemporary statistics with numerous printouts and exercises that can be solved with the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques.
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Review: Applied Regression Analysis and Other Multivariable Methods

User Review  - Lori - Goodreads

This was possibly one of the worst written statistics books ever. Not that I'm an expert, but for $200 I expected a little more. Equations were thrown in and there was a serious expectation of math ... Read full review

About the author (2007)

David G. Kleinbaum is Associate Professor of Biostatistics and Epidemiology at the University of North Carolina School of Public Health and holds a Ph.D. from the University of North Carolina.

Lawrence L. Kupper is Professor of Biostatistics and Epidemiology at the University of North Carolina School of Public Health and holds a Ph.D. from the University of North Carolina. Drs. Kleinbaum and Kupper have worked on the development of applications of statistical methods to epidemiology for over ten years. They have conducted several epidemiological research studies and published their work in Biometrics and the American Journal of Epidemiology, among others. Their short course on the subject of this book is in high demand in the U.S. and internationally. They are also the authors of Applied Regression Analysis (Duxbury Press, 1977).

Hal Morgenstern is Assistant Professor of Epidemiology at the Yale University School of Public Health. Dr. Morgenstern's work focuses on epidemiologic research methods and he has published extensively on the subject in the American Journal of Epidemiology, the International Journal of Epidemiology, Biometrics and the Journal of Community Health. Much of his research is applied to planning and policy issues, as well as to cardiovascular disease and to senile dementia. Dr. Morgenstern holds a Ph.D. in Epidemiology from the University of North Carolina, as well as degrees in Architecture from M.I.T. and in Regional Planning from the University of North Carolina.

Keith E. Muller, Ph.D., is Associate Professor of Biostatistics at the University of North Carolina at Chapel Hill. He teaches classes and seminars in the theory and practice of univariate and multivariate linear models with Gaussian errors. A SAS user since 1978, he is best known for his contributions to theory and practice of sample size and power calculations, including SAS/IML programs for power in repeated measures.

Bethel A. Fetterman, M.S., is Director of Clinical Data Processing and Analysis at PharmaLinkFHI in Research Triangle Park, North Carolina. She is currently on leave from the doctoral program in Biostatistics at the University of North Carolina at Chapel Hill. A SAS user since 1989, she uses SAS software in designing, managing, analyzing, and reporting clinical trials of new pharmaceutical.

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