Data handling and statistics essentials

There is a critical need for high-quality, rigorous out-o-hospital research to drive further developments in out-of-hospital medicine and to improve the quality of care and outcomes for patients served by emergency medical services. Appropriate data handling and statistical analyses are very important aspects of such high-quality research. In this chapter, we detail several related topics, including 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 and interim data analysis in clinical trials, multivariable analysis, clustered data, missing data, and strategies for using statistical consultants.