Handbook of Regression and Modeling

Applications for the Clinical and Pharmaceutical Industries

Daryl S. Paulson - Collection Chapman & Hall/CRC Biostatistics Series

502 pages, parution le 08/02/2007

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Résumé

Carefully 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.

Offers essential information for applying biostatistics to clinical and pharmaceutical research
Presents exploratory data analysis to evaluate the fit of the model to the actual data
Presents data sets in their entirety instead of relying on data sets supplied on a software CD
Provides a well-defined procedure for adding or subtracting independent variables to the model variables with methods that rely on computer software
Addresses practical issues such as cost, feasibility, model adequacy-testing, and forecasting
Covers regression analysis and modeling for assay development/validation, stability design and analysis, toxicology studies, and dose ranging and response

Sommaire

Basic Statistical Concepts
Simple Linear Regression
Special Problems in Simple Linear Regression: Serial Correlation and Curve Fitting
Multiple Linear Regression
Correlation Analysis in Multiple Regression
Some Important Issues in Multiple Linear Regression
Polynomial Regression
Special Topics in Multiple Regression
Indicator (Dummy) Variable Regression
Model Building and Model Selection
Analysis of Covariance

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Chapman and Hall / CRC
Auteur(s)	Daryl S. Paulson
Collection	Chapman & Hall/CRC Biostatistics Series
Parution	08/02/2007
Nb. de pages	502
Format	16 x 23,5
Couverture	Relié
Poids	800g
Intérieur	Noir et Blanc
EAN13	9781574446104
ISBN13	978-1-57444-610-4