Exercise: Using Test Information I
2022
This sample exercise and solution set supports the teaching pack on Using Test Information I, in which students review the performance of a dichotomous test and the relationship between sensitivity and specificity, calculate likelihood ratios to describe test performance, and conduct probability revision using the odds-LR form of Bayes. In addition to the sample exercise, materials include an instructor's note, videos, companion slides, a glossary, and an annotated bibliography.
Learning Objectives
- Calculate four conditional probabilities describing the performance of a dichotomous test, and explain the relationship between the TPR (sensitivity), FNR, TNR (specificity), and FPR.
- Define a likelihood ratio (LR), calculate & interpret LR for positive result (LR+) and for negative result (LR-).
- Convert odds to probabilities (and vice versa) & conduct probability revision using the odds-LR form of Bayes.
The exercise provides just 2-3 simple examples of the types of short questions that can be useful for practicing some of the skills covered in this teaching pack. These should be modified, tailored, and expanded upon to meet the goals of specific classes.
This teaching pack was developed by Sue J. Goldie at the Center for Health Decision Science, Harvard T.H. Chan School of Public Health. The multimedia components were developed as part of a series of pilots in the CHDS Media Hub, led by Jake Waxman, where media-based pedagogy experiments contribute to new ways of thinking about short form content.
Related Files:
Source:
Exercise. Teaching Pack: Using Test Information I. Center for Health Decision Science, Harvard T.H. Chan School of Public Health 2022. http://repository.chds.hsph.harvard.edu/repository/2723