Cargando…
Linear mixed models to handle missing at random data in trial‐based economic evaluations
Trial‐based cost‐effectiveness analyses (CEAs) are an important source of evidence in the assessment of health interventions. In these studies, cost and effectiveness outcomes are commonly measured at multiple time points, but some observations may be missing. Restricting the analysis to the partici...
Autores principales: | Gabrio, Andrea, Plumpton, Catrin, Banerjee, Sube, Leurent, Baptiste |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325521/ https://www.ncbi.nlm.nih.gov/pubmed/35368119 http://dx.doi.org/10.1002/hec.4510 |
Ejemplares similares
-
Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: A Review with Future Recommendations
por: Gabrio, Andrea, et al.
Publicado: (2017) -
The handling of missing data in trial-based economic evaluations: should data be multiply imputed prior to longitudinal linear mixed-model analyses?
por: Ben, Ângela Jornada, et al.
Publicado: (2022) -
Sensitivity analyses for trials with missing data, assuming missing not at random mechanisms
por: Leurent, Baptiste, et al.
Publicado: (2013) -
Erratum to: Handling Missing Data in Within-Trial Cost-Effectiveness Analysis: A Review with Future Recommendations
por: Gabrio, Andrea, et al.
Publicado: (2017) -
Missing data in trial‐based cost‐effectiveness analysis: An incomplete journey
por: Leurent, Baptiste, et al.
Publicado: (2018)