Statistics and experimental design for toxicologists and pharmacologists
著者
書誌事項
Statistics and experimental design for toxicologists and pharmacologists
Taylor & Francis, 2006
4th ed
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注記
Includes bibliographies and index
内容説明・目次
内容説明
Purposefully designed as a resource for practicing and student toxicologists, Statistics and Experimental Design for Toxicologists and Pharmacologists, Fourth Edition equips you for the regular statistical analysis of experimental data. Starting with the assumption of basic mathematical skills and knowledge, the author supplies a complete and systematic yet practical introduction to the statistical methodologists available for, and used in, the discipline. For every technique presented, a worked example from toxicology is also presented.
See what's new in the Fourth Edition:
The first practical guide to performing meta analysis allowing for using the power inherent in multiple similar studies
Coverage of Bayesian analysis and data analysis in pharmacology and toxicology
Almost 200 problems with solutions
Discussion of analysis of receptor binding assays, safety pharmacology assays and other standard types conducted in pharmacology
A new chapter explaining the basics of Good Laboratory Practices (GLPs)
For those with computer skills, this edition has been enhanced with the addition of basic SAS
Written specifically for toxicologists and pharmacologists, the author draws on more than 30 years of experience to provide understanding of the philosophical underpinnings for the overall structure of analysis. The book's organization fosters the ordered development of skills and yet still facilitates ease of access to information as needed. This Fourth Edition gives you the tools necessary to perform rigorous and critical analysis of experimental data and the insight to know when to use them.
目次
Introduction. Basic Principles Experimental Design. Software Programs. Methods for Data Collection, Preparation and Exploration. Hypothesis Testing: Categorical and Ranked Data. Hypothesis Testing: Univariate. Modeling and Extrapolation. Trend Analysis. Methods for Reduction of Dimensionality. Multivariate Methods. Meta Analysis. Bayesian Analysis. Data Analysis in Toxicology. Data Analysis for Pharmacology and Pharmokinetics. Carcinogenesis. Risk Assessment. Epidemiology. Structure Activity Relationships. Frontiers and Controversy. Appendices-Tables.
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