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Contrasting groups’ standard setting for consequences analysis in validity studies: reporting considerations
- Source :
- Advances in Simulation, Vol 3, Iss 1, Pp 1-7 (2018), Advances in Simulation, Jørgensen, M, Konge, L & Subhi, Y 2018, ' Contrasting groups' standard setting for consequences analysis in validity studies : reporting considerations ', Advances in Simulation, vol. 3, 5, pp. 1-7 . https://doi.org/10.1186/s41077-018-0064-7
- Publication Year :
- 2018
- Publisher :
- BMC, 2018.
-
Abstract
- Background The contrasting groups’ standard setting method is commonly used for consequences analysis in validity studies for performance in medicine and surgery. The method identifies a pass/fail cut-off score, from which it is possible to determine false positives and false negatives based on observed numbers in each group. Since groups in validity studies are often small, e.g., due to a limited number of experts, these analyses are sensitive to outliers on the normal distribution curve. Methods We propose that these shortcomings can be addressed in a simple manner using the cumulative distribution function. Results We demonstrate considerable absolute differences between the observed false positives/negatives and the theoretical false positives/negatives. In addition, several important examples are given. Conclusions We propose that a better reporting strategy is to report theoretical false positives and false negatives together with the observed false positives and negatives, and we have developed an Excel sheet to facilitate such calculations. Trial registration Not relevant. Electronic supplementary material The online version of this article (10.1186/s41077-018-0064-7) contains supplementary material, which is available to authorized users.
- Subjects :
- Medical education
False positives
Computer science
Methodology Article
Cumulative distribution function
False positives and false negatives
nutritional and metabolic diseases
General Medicine
Messick’s validity framework
lcsh:Computer applications to medicine. Medical informatics
nervous system diseases
Normal distribution
03 medical and health sciences
0302 clinical medicine
Standard setting
030220 oncology & carcinogenesis
Medicine public health
Outlier
Statistics
False positive paradox
False negatives
lcsh:R858-859.7
030211 gastroenterology & hepatology
Contrasting groups
Subjects
Details
- Language :
- English
- ISSN :
- 20590628
- Volume :
- 3
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Advances in Simulation
- Accession number :
- edsair.doi.dedup.....7bac8dac6790f37c6cba596d3f437c3c
- Full Text :
- https://doi.org/10.1186/s41077-018-0064-7