Cargando…
Multiple imputation methods for bivariate outcomes in cluster randomised trials
Missing observations are common in cluster randomised trials. The problem is exacerbated when modelling bivariate outcomes jointly, as the proportion of complete cases is often considerably smaller than the proportion having either of the outcomes fully observed. Approaches taken to handling such mi...
Autores principales: | DiazOrdaz, K., Kenward, M. G., Gomes, M., Grieve, R. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4981911/ https://www.ncbi.nlm.nih.gov/pubmed/26990655 http://dx.doi.org/10.1002/sim.6935 |
Ejemplares similares
-
A comparison of multiple imputation methods for bivariate hierarchical data: an application to cost-effectiveness analyse
por: Diaz-Ordaz, K, et al.
Publicado: (2013) -
Missing binary outcomes under covariate‐dependent missingness in cluster randomised trials
por: Hossain, Anower, et al.
Publicado: (2017) -
Methods for estimating complier average causal effects for cost‐effectiveness analysis
por: DiazOrdaz, K., et al.
Publicado: (2017) -
Complier-average causal effects for multivariate outcomes: an instrumental variable approach with application to health economics
por: DiazOrdaz, Karla, et al.
Publicado: (2015) -
Consent processes in cluster-randomised trials in residential facilities for older adults: a systematic review of reporting practices and proposed guidelines
por: DiazOrdaz, Karla, et al.
Publicado: (2013)