Statistical Methods Useful in Clinical Simulation and Medical Education Scholarship

• Main Authors: Zuber D. Mulla, J. Hector Aranda, Donovan Rojas, Sanja Kupesic Plavsic
• Format: Article
• Language: English
• Published: Marshall University 2019-10-01
• Series: Marshall Journal of Medicine
• Subjects: education; simulation; quality improvement; data analysis; epidemiology
• Online Access: https://mds.marshall.edu/cgi/viewcontent.cgi?article=1243&context=mjm

The objective of this paper is to introduce selected statistical and epidemiologic topics that are of interest to interdisciplinary teams of healthcare quality professionals, educators, technical staff, and researchers who participate in clinical simulation scholarship. Four research vignettes in the setting of a hypothetical clinical simulation training workshop are presented. The first vignette illustrates the utility of exact logistic regression when analyzing a small dataset. The second underscores the importance of using an appropriate method to account for the repeated measurement of an outcome. The third illustrates the use of the intraclass correlation coefficient to measure inter-rater reliability. The final vignette demonstrates the benefits of creating a causal diagram known as a directed acyclic graph.