Handling Missing Data in Health Economics and Outcomes Research (HEOR): A Systematic Review and Practical Recommendations

BACKGROUND: Missing data in costs and/or health outcomes and in confounding variables can create bias in the inference of health economics and outcomes research studies, which in turn can lead to inappropriate policies. Most of the literature focuses on handling missing data in randomized controlled...

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Detalles Bibliográficos
Autores principales: Mukherjee, Kumar, Gunsoy, Necdet B., Kristy, Rita M., Cappelleri, Joseph C., Roydhouse, Jessica, Stephenson, Judith J., Vanness, David J., Ramachandran, Sujith, Onwudiwe, Nneka C., Pentakota, Sri Ram, Karcher, Helene, Di Tanna, Gian Luca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Systematic Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635950/
https://www.ncbi.nlm.nih.gov/pubmed/37490207
http://dx.doi.org/10.1007/s40273-023-01297-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635950/
https://www.ncbi.nlm.nih.gov/pubmed/37490207
http://dx.doi.org/10.1007/s40273-023-01297-0

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