1st Edition
Principles of Experimental Design for the Life Sciences
Let this down-to-earth book be your guide to the statistical integrity of your work. Without relying on the detailed and complex mathematical explanations found in many other statistical texts, Principles of Experimental Design for the Life Sciences teaches how to design, conduct, and interpret top-notch life science studies. Learn about the planning of biomedical studies, the principles of statistical design, sample size estimation, common designs in biological experiments, sequential clinical trials, high dimensional designs and process optimization, and the correspondence between objectives, design, and analysis. Each of these important topics is presented in an understandable and non-technical manner, free of statistical jargon and formulas.
Written by a biostatistical consultant with 25 years of experience, Principles of Experimental Design for the Life Sciences is filled with real-life examples from the author's work that you can quickly and easily apply to your own. These examples illustrate the main concepts of experimental design and cover a broad range of application areas in both clinical and nonclinical research. With this one innovative, helpful book you can improve your understanding of statistics, enhance your confidence in your results, and, at long last, shake off those statistical shackles!
Planning Biomedical Studies
Study Objectives
The Planning Process
Writing Protocol
Correspondence Between Objectives, Design, and Analysis
Principles of Statistical Design
Bias and Variability
Identifying and Quantifying Sources of Bias and Vulnerability
Methods to Control Bias and Variability
Defining the Experimental Unit
Randomization
Uniformity Trials
Blocking
Blinding
Sample Size Estimation
Statistical Context
Sample Sizes for Point Estimation
Sample Sizes for Interval Estimation
Sample Sizes for Hypothesis Testing
Pilot Studies
Subsampling Issues
Sensitivity Analyses
Common Designs in Biological Experimentation
The Completely Randomized Design
Stratified Design/Randomized Block Design
Crossover Study
Split Plot Design
Types of Control
Dose Selection in Dose-Response Studies
Multicenter Studies
Summary
Sequential Clinical Trials
History
Rationale
Sequential Designs
Group Sequential Designs
Interim Analyses
Data Monitoring Boards
High Dimensional Designs and Process Optimization
Fractional Factorial Design
Response Surface Methodology
Process Optimization
The Correspondence Between Objectives, Design, and Analysis - Revisited
Data Analyses vs. Study Objectives and Design
Types of Data
Verification of Assumptions
Multiplicity Adjustments
Statistical Packages
Analysis Strategies
Meta Analysis
Summary and Concluding Remarks
The Role of the Statistician
Summary
Concluding Remarks
References
Appendix A: Glossary of Statistical Terms
Appendix B: Formulas for Sample Size Estimation
Index
Biography
Murray R. Selwyn
