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
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Quantitative Benefit-Risk Assessment in Medical Product Decision Making
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Machine Learning Methods in Health Economics and Outcomes Research—The PALISADE Checklist
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Opportunities and Barriers to the Development and Use of Open Source Health Economic Models: A Survey
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Modeling Good Research Practices - Overview: Report 1
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Interpreting Indirect Treatment Comparisons and Network Meta-Analysis for Health-Care Decision Making Report 1
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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