Resources Repository
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Tutorial/PrimerWeb Portal, Teaching Resource 2015Decision Theory
This chapter on normative decision theory is from the Stanford Encyclopedia of Philosophy, a dynamic reference …
This chapter on normative decision theory is from the Stanford Encyclopedia of Philosophy, a dynamic reference work available online. Decision theory is concerned with the reasoning underlying an person's choices, whether a mundane choice between taking the bus or getting a taxi, or a more far-reaching choice about whether to pursue a demanding political career. The orthodox normative decision theory, expected utility (EU) theory, essentially says that, in situations of uncertainty, one should prefer the option…
Decision Theory | Preferences/Values | Economics/Finance | Graduate | Doctoral | Critical Thinking/Analysis | Quantitative Literacy -
ReviewPublication 2017Patients' Preferences in Cancer Treatment: Review of Discrete Choice Experiments
This study aimed to systematically review discrete choice experiments (DCEs) about patients’ preferences for cancer …
This study aimed to systematically review discrete choice experiments (DCEs) about patients’ preferences for cancer treatment and assessed the relative importance of outcome, process and cost attributes. A systematic literature review was conducted using PubMed and EMBASE to identify all DCEs investigating patients’ preferences for cancer treatment between January 2010 and April 2016. Attributes were classified into outcome, process and cost attributes, and their relative importance was assessed. A total of 28 DCEs were identified.…
Decision Analysis | Preferences/Values | Health Outcomes | Cost-Effectiveness Analysis | Chronic Disease/Risk | Health Systems | Economics/Finance | Health/Medicine | North America | Europe -
Resource PortalWeb Portal, Teaching Resource 2024Decision Sciences Institute
The Decision Sciences Institute (DSI) was founded in 1968 as the American Institute for the …
The Decision Sciences Institute (DSI) was founded in 1968 as the American Institute for the Decision Sciences (renamed to the Decision Science Institute in 1986). DSI is an independent non-profit organization with a mission to enrich the discipline of decision sciences and improve educational programs and instruction in decision sciences. DSI conducts annual meetings at the national and the regional levels, and produces a monthly news publication called “Decision Line” as well as two journals,…
Decision Analysis | Operations Research | Business/Industry | Climate/Environment | Health/Medicine | Global | College | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Quantitative Literacy -
Tutorial/PrimerPublication, Teaching Resource 2017Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software
This is a user guide on the analysis of data (including best-worst and best-best data) …
This is a user guide on the analysis of data (including best-worst and best-best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. Authors also provide a review of standard software. Authors argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of…
Decision Analysis | Preferences/Values | Health Outcomes | Economics/Finance | Health/Medicine | Graduate | Doctoral | Professional | Quantitative Literacy -
Tutorial/PrimerPublication, Teaching Resource 2014Decision Theory: A Formal Philosophical Introduction
Decision theory is the study of how choices are and should be made in a …
Decision theory is the study of how choices are and should be made in a variety of different contexts. The author approaches the topic from a formal-philosophical point of view with a focus on normative and conceptual issues. After considering the question of how decision problems should be framed, he examines both the standard theories of chance under conditions of certainty, risk and uncertainty and some of the current debates about how uncertainty should be measured and how…
Decision Theory | Preferences/Values | Economics/Finance | Doctoral | Critical Thinking/Analysis | Quantitative Literacy -
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 -
ArticlePublication 2017Using Data-Driven Agent-Based Models to Forecast Emerging Infectious Diseases
This paper describes an agent-based model framework developed to forecast the 2014-15 Ebola epidemic, which …
This paper describes an agent-based model framework developed to forecast the 2014-15 Ebola epidemic, which was subsequently used in the Ebola forecasting challenge. Producing timely and reliable forecasts for an epidemic of an emerging infectious disease is a challenge. Epidemiologists and policy makers have to deal with poor data quality, limited understanding of the disease dynamics, a rapidly changing social environment and the uncertainty around the effects of various interventions in place. In this setting,…
Calibration/Validation | Microsimulation | Dynamic Simulation | Infectious Diseases | Health/Medicine | Sub-Saharan Africa -
ReviewPublication 2017Validation and Calibration of Structural Models that Combine Information from Multiple Sources
This is a review of calibration and validation methods in mathematical modeling. Such models that …
This is a review of calibration and validation methods in mathematical modeling. Such models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. The authors provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves…
Calibration/Validation | Mathematical Models | Health/Medicine -
ArticlePublication 2017Likelihood Approach for Calibration of Stochastic Epidemic Models
Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens …
Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens given the importance of chance events when the number of infectious individuals is small. However, methods for parameter estimation and prediction for these types of stochastic models remain limited. This paper describes a calibration and prediction framework for stochastic compartmental transmission models of epidemics. The proposed method applies a linear noise approximation to describe the size of the fluctuations, and…
Calibration/Validation | Dynamic Transmission | Dynamic Simulation | Infectious Diseases | Health Systems | Health/Medicine | Global