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Principles of Experimental Design for the Life Sciences: 1st Edition (Hardback) book cover

Principles of Experimental Design for the Life Sciences

1st Edition

By Murray R. Selwyn

CRC Press

176 pages

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Hardback: 9780849394614
pub: 1996-05-23
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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!

Table of Contents

Introduction and Overview

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


Uniformity Trials



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


Sequential Clinical Trials



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


Concluding Remarks


Appendix A: Glossary of Statistical Terms

Appendix B: Formulas for Sample Size Estimation


Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
SCIENCE / Research & Methodology