Books  Data Analysis & Modelling  Data Analysis & Statistics 

Principles of Experimental Design for the Life Sciences

Handbook / Manual

By: Murray R Selwyn

160 pages, Figs, tabs

CRC Press

Hardback | Dec 1996 | #88914 | ISBN: 0849394619
Temporarily out of stock: order now to get this when available Details
NHBS Price: £47.99 $62/€53 approx

About this book

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!


Introduction and OverviewPlanning Biomedical StudiesStudy ObjectivesThe Planning ProcessWriting ProtocolCorrespondence Between Objectives, Design, and AnalysisPrinciples of Statistical DesignBias and VariabilityIdentifying and Quantifying Sources of Bias and VulnerabilityMethods to Control Bias and VariabilityDefining the Experimental UnitRandomizationUniformity TrialsBlockingBlindingSample Size EstimationStatistical ContextSample Sizes for Point EstimationSample Sizes for Interval EstimationSample Sizes for Hypothesis TestingPilot StudiesSubsampling IssuesSensitivity AnalysesCommon Designs in Biological ExperimentationThe Completely Randomized DesignStratified Design/Randomized Block DesignCrossover StudySplit Plot DesignTypes of ControlDose Selection in Dose-Response StudiesMulticenter StudiesSummarySequential Clinical TrialsHistoryRationaleSequential DesignsGroup Sequential DesignsInterim AnalysesData Monitoring BoardsHigh Dimensional Designs and Process OptimizationFractional Factorial DesignResponse Surface MethodologyProcess OptimizationThe Correspondence Between Objectives, Design, and Analysis - RevisitedData Analyses vs. Study Objectives and DesignTypes of DataVerification of AssumptionsMultiplicity AdjustmentsStatistical PackagesAnalysis StrategiesMeta AnalysisSummary and Concluding RemarksThe Role of the StatisticianSummaryConcluding RemarksReferencesAppendix A: Glossary of Statistical TermsAppendix B: Formulas for Sample Size EstimationIndex

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