About Methodology
Rigorous and proven methodologies are essential to the field of health economics and outcomes research. Topics include a variety of methodological and statistical arenas, including artificial intelligence, machine learning, predictive analytics, missing data, confounding, selection bias correction, causal inference, modeling and simulation, patient-reported outcomes, and survey methods.
Related ISPOR Reports & Resources
-
Quantitative Benefit-Risk Assessment in Medical Product Decision Making
-
Machine Learning Methods in Health Economics and Outcomes Research—The PALISADE Checklist
-
Opportunities and Barriers to the Development and Use of Open Source Health Economic Models: A Survey
-
Modeling Good Research Practices - Overview: Report 1
-
Interpreting Indirect Treatment Comparisons and Network Meta-Analysis for Health-Care Decision Making Report 1
-
Recommendations on Evidence Needed to Support Measurement Equivalence between Electronic and Paper-Based Patient-Reported Outcome (PRO) Measures
RELATED ISPOR PUBLICATIONS
HEOR Articles
The Role of Education in Shaping an Open-Source Future
The Role of Education in Shaping an Open-Source Future
RELATED EVENTS
ALL METHODOLOGY RESULTS
EDUCATIONAL OPPORTUNITIES
7e0f57a8009346f085790211b3b70ba6.png?sfvrsn=db07ec15_0 "cta1-(1)7e0f57a8009346f085790211b3b70ba6")
