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OverviewCarefully designed for use by clinical and pharmaceutical researchers and scientists, Handbook of Regression Analysis and Modeling explores statistical methods that have been adapted into biological applications for the quickly evolving field of biostatistics. The author clearly delineates a six-step method for hypothesis testing using data that mimics real life. Relying heavily on computer software, he includes exploratory data analysis to evaluate the fit of the model to the actual data. The book presents a well-defined procedure for adding or subtracting independent variables to the model variable and covers how to apply statistical forecasting methods to the serially correlated data characteristically found in clinical and pharmaceutical settings. The stand alone chapters allow you to pick and choose which chapter to read first and home in on the information that fits your immediate needs. Each example is presented in computer software format. The author uses MINITAB in the book but supplies instructions for SAS and SPSSX, making the book easily adaptable to individual situations. Although written with the assumption that the reader has knowledge of basic and matrix algebra, the book supplies a short course on matrix algebra in the appendix for those who need it. Covering more than just statistical theory, the book provides advanced methods that you can put to immediate use. Full Product DetailsAuthor: Daryl S. Paulson , Shein-Chung Chow (Duke Univ, USA)Publisher: Taylor & Francis Inc Imprint: CRC Press Inc Dimensions: Width: 15.20cm , Height: 3.20cm , Length: 22.90cm Weight: 1.120kg ISBN: 9781574446104ISBN 10: 157444610 Pages: 520 Publication Date: 19 December 2006 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsBasic Statistical Concepts. Simple Linear Regression. Special Problems in Simple Linear Regression. Some Aspects and Examples in Constructing a Valid Simple Regression Study. Multiple Linear Regression. Correlation in Multiple Regression. Issues in Multiple Linear Regression. Polynomial Regression. Special Topics in Multiple Regression. Indicator (Dummy) Variable Regression. Model Building/Model Selection. Analysis of Covariance. Logistic Regression.ReviewsUnlike many other statistical texts, Paulson't book is easy to read and comprehend. It moves the reader along the statistics learning path with much less trauma. The author takes great care to explain the logic behind the statistical analysis process as well as disclose the benefits associated with the effort. Paulson's addition of carefully selected philosophic nuggets gives certain passages of the text a delightful 'Zen' quality that is very refreshing. I enjoyed the reading experience and will use the text in my own work. - Lawton A. Seal, Healthpoint/DEB Pharmaceuticals many other statistical texts, Paulson't book is easy to read and comprehend. It moves the reader along the statistics learning path with much less trauma. The author takes great care to explain the logic behind the statistical analysis process as well as disclose the benefits associated with the effort. Paulson's addition of carefully selected philosophic nuggets gives certain passages of the text a delightful 'Zen' quality that is very refreshing. I enjoyed the reading experience and will use the text in my own work. - Lawton A. Seal, Healthpoint/DEB Pharmaceuticals Author InformationDaryl S. Paulson Tab Content 6Author Website:Countries AvailableAll regions |