Written for animal researchers, this book provides a comprehensive guide to the design and statistical analysis of animal experiments. It has long been recognised that the proper implementation of these techniques helps reduce the number of animals needed. By using real-life examples to make them more accessible, this book explains the statistical tools employed by practitioners. A wide range of design types are considered, including block, factorial, nested, cross-over, dose-escalation and repeated measures and techniques are introduced to analyse the experimental data generated. Each analysis technique is described in non-mathematical terms, helping readers without a statistical background to understand key techniques such as t-tests, ANOVA, repeated measures, analysis of covariance, multiple comparison tests, non-parametric and survival analysis. This is also the first text to describe technical aspects of InVivoStat, a powerful open-source software package developed by the authors to enable animal researchers to analyse their data and obtain informative results.
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Product Details
Weight: 720g
Dimensions: 188 x 245mm
Publication Date: 13 Mar 2014
Publisher: Cambridge University Press
Publication City/Country: United Kingdom
Language: English
ISBN13: 9781107690943
About Robin A. ClarkSimon T. Bate
Simon T. Bate is a Principal Statistician at GlaxoSmithKline supporting pre-clinical research. He has spent over 12 years supporting the design and statistical analysis of animal experiments including drug discovery research toxicology studies and safety assessment. He presents many statistics courses around Europe including the statistics module of the British Association for Psychopharmacology's Pre-Clinical Certificate. Robin A. Clark is a Senior Analyst Programmer at Huntingdon Life Sciences Alconbury. Originally qualified as a marine ecologist he is now a software architect producing data collection and statistical applications for the pharmaceutical industry. Robin produced the WindowsTM GUI and designed the system architecture for InVivoStat.