Statistical concepts for research in emergency medical services

Craig D. Newgard, Roger J. Lewis

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

There is a critical need for high-quality, rigorous out-of-hospital research to drive further developments in out-of-hospital medicine and to improve the quality of care and outcomes for patients served by EMS. For this research to be valid and meaningful, it must be built on a foundation of appropriate statistical design and data interpretation. In this chapter, we address classical hypothesis testing, type I and II error, power analysis, commonly used statistical tests and their underlying assumptions, confidence intervals, multiple comparisons, subgroup analysis, intention-to-treat, interim data analysis in clinical trials, multivariable analysis, clustered data, missing data, and strategies for using statistical consultants.

Original languageEnglish (US)
Title of host publicationMedical oversight of EMS
Publisherwiley
Pages500-509
Number of pages10
Volume2-2
ISBN (Electronic)9781119756279
ISBN (Print)9781119756248
DOIs
StatePublished - Aug 18 2021

Keywords

  • Analysis
  • Confidence intervals
  • Data
  • Intention-to-treat
  • Multivariable analysis
  • P-values
  • Statistics
  • Subgroup analysis
  • Type I error
  • Type II error

ASJC Scopus subject areas

  • General Medicine

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