Resources Repository
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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 -
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 -
Tutorial/PrimerPublication, Teaching Resource 2017Guide to Regulatory Impact Analysis
Regulatory impact analyses (RIAs) weigh the benefits of regulations against the burdens they impose and …
Regulatory impact analyses (RIAs) weigh the benefits of regulations against the burdens they impose and are invaluable tools for informing decision makers. The Consumer’s Guide to Regulatory Impact Analysis: Ten Tips for Being an Informed Policymaker offers 10 tips for non-specialist policymakers and interested stakeholders who will be reading RIAs as consumers.
Risk Analysis | Benefit-Cost Analysis | Government/Law | Global -
Tutorial/PrimerPublication, Teaching Resource 2017Bayesian Methods for Calibrating Health Policy Models: A Tutorial
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical …
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical basis for Bayesian calibration approaches as well as pragmatic considerations that arise in the tasks of creating calibration targets, estimating the posterior distribution, and obtaining results to inform the policy decision. These considerations, as well as the specific steps for implementing the calibration, are described in the context of an extended worked example about the policy choice to provide (or…
Calibration/Validation | Infectious Diseases | Health/Medicine -
Tutorial/PrimerPublication, Teaching Resource 2015Calibration of Complex Models through Bayesian Evidence Synthesis: A Tutorial
This tutorial demonstrates how to implement a Bayesian synthesis of diverse sources of evidence to …
This tutorial demonstrates how to implement a Bayesian synthesis of diverse sources of evidence to calibrate the parameters of a complex model. To illustrate these methods, the authors demonstrate how a previously developed Markov model for the progression of human papillomavirus (HPV-16) infection was rebuilt in a Bayesian framework. Transition probabilities between states of disease severity are inferred indirectly from cross-sectional observations of prevalence of HPV-16 and HPV-16–related disease by age, cervical cancer incidence, and…
Calibration/Validation | Infectious Diseases -
Tutorial/PrimerPublication, Teaching Resource 2005Refining Clinical Diagnosis with Likelihood Ratios
This article serves as a concise tutorial about the interpretation and use of likelihood ratios …
This article serves as a concise tutorial about the interpretation and use of likelihood ratios in clinical decision-making. Likelihood ratios can refine clinical diagnosis on the basis of signs and symptoms; however, they are underused for patients' care. A likelihood ratio is the percentage of ill people with a given test result divided by the percentage of well individuals with the same result. Ideally, abnormal test results should be much more typical in ill individuals…
Test Performance | Value of Information | Health/Medicine -
Tutorial/PrimerPublication, Teaching Resource 1980Threshold Approach to Clinical Decision Making
This classic paper provides a "tutorial" for students learning about diagnostic testing, probability revision, and …
This classic paper provides a "tutorial" for students learning about diagnostic testing, probability revision, and how to calculate thresholds for testing, treatment, and no treatment. The authors describe how a physician's estimate of the probability that a patient has a particular disease is a principal factor in the determination of whether to withhold treatment, obtain more data by testing, or treat without subjecting the patient to the risks of further diagnostic tests. Using the concepts of decision analysis,…
Test Performance | Probability/Bayes | Value of Information | Decision Analysis | Health/Medicine