Analysis of Variance and Covariance
How to Choose and Construct Models for the Life Sciences
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Product details:
- Publisher Cambridge University Press
- Date of Publication 30 August 2007
- ISBN 9780521684477
- Binding Paperback
- No. of pages304 pages
- Size 228x153x16 mm
- Weight 496 g
- Language English
- Illustrations 62 b/w illus. 95 tables 0
Categories
Short description:
A concise, systematic introduction to the principles of analysis of variance for post-graduates and professionals.
MoreLong description:
Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.
'This is an authoritatively written book aimed at people who already have a good grasp of analysis of (co)variance using fixed factor an(c)ova, who are not afraid of algebraic notation and who wish to understand the background to the comprehensive range of study designs described which incorporate covariates and random factors.' Psychological Medicine
Table of Contents:
Preface; Introduction to analysis of variance; Introduction to model structures; Part I. Model Structures: 1. One-factor designs; 2. Nested designs; 3. Fully replicated factorial designs; 4. Randomised block designs; 5. Split plot designs; 6. Repeated measures designs; 7. Unreplicated designs; Part II. Further Topics: 8. Further topics; 9. Choosing experimental designs; 10. Best practice in presentation of the design; 11. Troubleshooting problems during analysis; Glossary; Categories of model; Bibliography; Index of all ANOVA models with up to three factors; Index.
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