Sample Sizes for Clinical, Laboratory and Epidemiology Studies

David Machin, Michael J. Campbell, Say Beng Tan, Sze Huey Tan

• Publisher: Wiley-Blackwell
• Year: 2018
• Print ISBN: 9781118874943
• eBook ISBN: 9781118874936
• Edition: 4
• Topic: Medicine
• Subtopic: Medical Theory, Practice & Reference

An authoritative resource that offers the statistical tools and software needed to design and plan valid clinical studies

Now in its fourth and extended edition, Sample Sizes for Clinical, Laboratory and Epidemiology Studiesincludes the sample size software (SSS) and formulae and numerical tables needed to design valid clinical studies. The text covers clinical as well as laboratory and epidemiology studies and contains the information needed to ensure a study will form a valid contribution to medical research. 

The authors, noted experts in the field, explain step by step and explore the wide range of considerations necessary to assist investigational teams when deriving an appropriate sample size for their when planned study. The book contains sets of sample size tables with companion explanations and clear worked out examples based on real data. In addition, the text offers bibliography and references sections that are designed to be helpful with guidance on the principles discussed.

This revised fourth edition:

• Offers the only text available to include sample size software for use in designing and planning clinical studies
• Presents new and extended chapters with many additional and refreshed examples
• Includes clear explanations of the principles and methodologies involved with relevant practical examples
• Makes clear a complex but vital topic that is designed to ensure valid methodology and publishable results 
• Contains guidance from an internationally recognised team of medical statistics experts

Written for medical researchers from all specialities and medical statisticians, Sample Sizes for Clinical, Laboratory and EpidemiologyStudies offers an updated fourth edition of the important guide for designing and planning reliable and evidence based clinical studies.

1
Basic Design Considerations

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SUMMARY

This chapter reviews the reasons why sample size considerations are important when planning a clinical study of any type. The basic elements underlying this process include the null and alternative study hypotheses, effect size, statistical significance level and power, each of which are described. We introduce the notation to distinguish the population parameters we are trying to estimate with the study, from their anticipated value at the planning stages and also from their estimated value once the study has been completed. We emphasise for comparative studies that, whenever feasible, it is important to randomise the allocation of subjects to respective groups.

The basic properties of the standardised Normal distribution are described. Also discussed is how, once the effect size, statistical significance level and power for a comparative study using a continuous outcome are specified, the Fundamental Equation (which essentially plays a role in most sample size calculations for comparative studies) is derived.

The Student’s t‐distribution and the Non‐central t‐distribution are also described. In addition the Binomial, Poisson, Negative‐Binomial, Beta and Exponential statistical distributions are defined. In particular, the circumstances (essentially large study sizes) in which the Binomial and Poisson distributions have an approximately Normal shape are described. Methods for calculating confidence intervals for a population mean are indicated together with (suitably modified) how they can be used for a proportion or a rate in larger studies. For the Binomial situation, formulae are also provided where the sample size is not large. Finally, a note concerning numerical accuracy of the calculations in the illustrative examples of later chapters is included.

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1.1 Why Sample Size Calculations?

To motivate the statistical issues relevant to sample size calculations, we will assume that we are planning a two‐group clinical trial in which subjects are allocated at random to one of two alternative treatments for a particular medical condition and that a single endpoint measure has been specified in advance. However, it should be emph...

Table of contents

• Cover
• Table of Contents
• Preface
• 1 Basic Design Considerations
• 2 Further Design Considerations
• 3 Binary Outcomes
• 4 Ordered Categorical Outcomes
• 5 Continuous Outcomes
• 6 Rate Outcomes
• 7 Survival Time Outcomes
• 8 Paired Binary, Ordered Categorical and Continuous Outcomes
• 9 Confidence Intervals
• 10 Repeated Outcome Measures
• 11 Non-Inferiority and Equivalence
• 12 Cluster Designs
• 13 Stepped Wedge Designs
• 14 More than Two Groups Designs
• 15 Genomic Targets and Dose-Finding
• 16 Feasibility and Pilot Studies
• 17 Therapeutic Exploratory Trials
• 18 Therapeutic Exploratory Trials
• 19 The Correlation Coefficient
• 20 Observer Agreement Studies
• 21 Reference Intervals and Receiver Operating Curves
• 22 Sample Size Software
• Cumulative References
• Index
• End User License Agreement