Statistical reasoning in medicine

Statistical reasoning in medicine: the intuitive P-value primer

by Moyé, Lemuel A.

Type Book
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Statistical Reasoning in Medicine: The Intuitive P-value Primer, with its emphasis on patient and community protection, illustrates the correct use of statistics in health care research for healthcare workers. Through clear explanations and examples, this book provides the non-mathematician with a foundation for understanding the underlying statistical reasoning process in clinical research, the core principles of research design, and the correct use of statistical inference and p-values.

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Title Statements

  • Full title :Statistical reasoning in medicine : the intuitive P-value primer / Lemuel A. Moyé.

Summary

Statistical Reasoning in Medicine: The Intuitive P-value Primer, with its emphasis on patient and community protection, illustrates the correct use of statistics in health care research for healthcare workers. Through clear explanations and examples, this book provides the non-mathematician with a foundation for understanding the underlying statistical reasoning process in clinical research, the core principles of research design, and the correct use of statistical inference and p-values.

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Edition Statements

  • Publication Date:©2006.
  • Edition:2nd ed

Publication Statements

  • Publisher(s):Springer
  • Place of Publication:New York
  • Language:eng
  • Publication Date:©2006.

The Physical Object

  • Description:xx, 301 pages : : illustrations ; : 24 cm

Edition Identifiers

  • ISBN:9780387329130, 0387329137
  • oclc:ocm76481793
  • LC Classification:R853.S7
  • Dewey Decimal:610/.7/27

Table of Contents

Basis of statistical reasoning in medicine -- Search versus research -- Hypothesis-testing primer -- Mistaken identity: P-values in epidemiology -- Shrine worship -- P-values, power, and efficacy -- Scientific reasoning, P-values, and the court -- One-sided versus two-sided testing -- Multiple testing and combined endpoints -- Subgroup analyses -- P-values and regression analyses -- Bayesian analysis: posterior P-values -- Conclusions -- Standard normal probabilities -- Sample size primer -- Daubert and rule 702 factors.

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