Sample Sizes for Clinical, Laboratory and Epidemiology Studies
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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 expertsWritten 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.
David Machin, Leicester Cancer Research Centre, University of Leicester, Leicester and Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, UK.
Michael J. Campbell, Medical Statistics Group, School of Health and Related Research, University of Sheffield, Sheffield, UK.
Say Beng Tan, SingHealth Duke-NUS Academic Medical Centre, Singapore.
Sze Huey Tan, Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre, Singapore.
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