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Guide to Sample Size for Animal-based Studies [Minkštas viršelis]

(University of Florida, Gainesville, Florida, USA)
  • Formatas: Paperback / softback, 288 pages, aukštis x plotis x storis: 244x170x113 mm, weight: 709 g
  • Išleidimo metai: 22-Sep-2023
  • Leidėjas: Wiley-Blackwell
  • ISBN-10: 111979997X
  • ISBN-13: 9781119799979
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 288 pages, aukštis x plotis x storis: 244x170x113 mm, weight: 709 g
  • Išleidimo metai: 22-Sep-2023
  • Leidėjas: Wiley-Blackwell
  • ISBN-10: 111979997X
  • ISBN-13: 9781119799979
Kitos knygos pagal šią temą:
"How large a sample size do I need for my study"? Although one of the most commonly-asked questions in statistics, the importance of proper sample size estimation seems to be overlooked by many preclinical researchers. Over the past two decades, numerousreviews of the published literature indicate many studies are too small to answer the research question and results are too unreliable to be trusted. Few published studies present adequate justification of their chosen sample sizes, or even report the total number of animals used. On the other hand, it is not unusual for protocols (usually those involving mouse models) to request preposterous numbers of animals, sometimes in the tens or even hundreds of thousands, "because this is an exploratory study, so it is unknown how many animals we will require"--

Understand a foundational area of experimental design with this innovative reference

Animal-based research is an essential part of basic and preclinical research, but poses a unique set of experimental design challenges. The most important of these are the 3Rs Replacement, Reduction and Refinement the principles comprising the ethical framework for humane animal-based studies. However, many researchers have difficulty navigating the design trade-offs necessary to simultaneously minimize animal use, and produce scientific information that is both rigorous and reliable.

A Guide to Sample Size for Animal-Based Studies meets this need with a thorough, accessible reference work to the subject. This book provides a straightforward systematic approach to "right-sizing" animal-based experiments, with sample size estimates based on the fundamentals of statistical thinking: structured research questions, variation control and appropriate design of experiments. The result is a much-needed guide to planning animal-based experiments to ensure scientifically valid and reliable results.

This book offers:

  • Step-by-step guidance in diverse methods for approximating and refining sample size
  • Detailed treatment of research topics specific to animal-based research, including pilot, feasibility and proof-of-concept studies
  • Sample size approximation methods for different types of data binary, continuous, ordinal, time to event and different study types description, comparison, nested designs, reference interval construction and dose-response studies
  • Numerous worked examples, using real data from published papers, together with SAS and R code

A Guide to Sample Size for Animal-Based Studies is a must-have reference for preclinical and veterinary researchers, as well as ethical oversight committees and policymakers.

Preface

Acknowledgements

Part I. What is sample size?

1. Introduction: The sample size problem in animal-based research

2. Sample size basics

3. Ten strategies to increase information (and reduce animal numbers)

Part II. Sample size for feasibility and pilot studies

4. Introduction to pilot studies

5. Operational pilots

6. Empirical and translational pilots

7. Feasibility calculations: Arithmetic estimation

8. Feasibility calculations: Probability-based estimation

Part III. Sample size for description

9. Introduction to descriptive studies

10. Confidence intervals

11. Prediction intervals

12. Tolerance intervals

13. Reference intervals

Part IV. Sample size for comparison

14. Hypothesis testing, power, non-centrality

15. A bestiary of effect sizes

16. Comparing two groups: Continuous outcomes

17. Comparing two groups: Binary and count outcomes

18. Comparing two groups: Time to event outcomes

19. Comparing multiple factors

20. Multi-level and hierarchical designs

21. Ordinal data

22. Dose-response studies

Index

Penny S. Reynolds, PhD, is a Research Assistant Professor in the Department of Anesthesiology, College of Medicine, and Department of Small Animal Clinical Sciences, College of Veterinary Medicine, University of Florida, USA.