Resources Repository
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Teaching PackWeb Portal, Teaching Resource 2023Teaching Pack: Heuristics with Joe Pliskin
This teaching pack, curated by the Center for Health Decision Science, features videos introducing heuristics …
This teaching pack, curated by the Center for Health Decision Science, features videos introducing heuristics used in decision making. While these “mental shortcuts” can be useful in some circumstances, they can lead to more errors than deliberate, rational thinking. An awareness of these heuristics is useful to decision makers. This series of videos on heuristics was developed by Professor Joe Pliskin during his residency with the CHDS Media Hub led by Jake Waxman. They reflect…
Decision Theory | Decision Psychology | Probability/Bayes | Preferences/Values | Chronic Disease/Risk | Clinical Care | Business/Industry | Economics/Finance | Health/Medicine | High School | College | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Decision Making/Leadership | Quantitative Literacy -
Teaching PackPublication, Teaching Resource 2022Teaching Pack: Using Test Information I
In this teaching pack on Using Test Information I, students review the performance of a …
In this teaching pack on Using Test Information I, 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. Materials include an instructor's note, videos, companion slides, a glossary, an annotated bibliography, and sample exercises. Learning Objectives Calculate four conditional probabilities describing the performance of a dichotomous test, and explain the…
Test Performance | Probability/Bayes | Decision Analysis | Child/Nutrition | Health/Medicine | College | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Graphics/Visualization | Quantitative Literacy -
Teaching PackPublication, Teaching Resource 2022Teaching Pack: Using Test Information II
In this teaching pack on Using Test Information II, students are introduced to tests with …
In this teaching pack on Using Test Information II, students are introduced to tests with continuous or categorical results, and calculate the sensitivity and specificity conditional on different 'cutoff points' or 'positivity criterion'. They are introduced to ROC curves and explore the implications of operating at different parts of the curve for any single test. They calculate the optimal positivity criterion given information on the prior, the test performance, and the relative consequences of true…
Test Performance | Probability/Bayes | Decision Analysis | Health/Medicine | College | Graduate | Doctoral | Critical Thinking/Analysis | Quantitative Literacy -
Teaching PackWeb Portal, Teaching Resource 2018Teaching Pack: Teaching Prototypes for Decision Analysis
These videos, developed by Professor Myriam Hunink during an immersion residency at the Center for …
These videos, developed by Professor Myriam Hunink during an immersion residency at the Center for Health Decision Science (CHDS) Media Hub, reflect experiments to augment brick and mortar teaching with multimedia materials that emphasize visualization of basic concepts. The first video introduces decision making under uncertainty, and illustrates the use of probability and odds to quantitatively express uncertainty. The second and third videos introduce probability revision visually and analytically, showing how an initial probability is…
Test Performance | Probability/Bayes | Value of Information | Chronic Disease/Risk | Health Systems | Health/Medicine | North America | Europe | High School | College | Graduate | Doctoral | Critical Thinking/Analysis | Graphics/Visualization | Quantitative Literacy -
Teaching PackPublication, Teaching Resource 2022Teaching Pack: Probability Revision and Bayes
In this teaching pack on Probability Revision and Bayes, students are introduced to the implications …
In this teaching pack on Probability Revision and Bayes, students are introduced to the implications of imperfect information, acquire a conceptual understanding of Bayes theorem, and gain practical skills in performing probability revision. Materials include an instructor's note, videos, companion slides, a glossary, an annotated bibliography, sample exercises, and additional support. Learning Objectives Demonstrate a conceptual understanding of Bayes’ theorem and probability revision. Differentiate between test characteristics (e.g., probability of positive test given…
Test Performance | Probability/Bayes | Decision Analysis | Environmental Health | Health/Medicine | College | Graduate | Critical Thinking/Analysis | Graphics/Visualization | Quantitative Literacy