Cargando…
Linear Increments with Non‐monotone Missing Data and Measurement Error
Linear increments (LI) are used to analyse repeated outcome data with missing values. Previously, two LI methods have been proposed, one allowing non‐monotone missingness but not independent measurement error and one allowing independent measurement error but only monotone missingness. In both, it w...
Autores principales: | Seaman, Shaun R., Farewell, Daniel, White, Ian 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/PMC5111617/ https://www.ncbi.nlm.nih.gov/pubmed/27867251 http://dx.doi.org/10.1111/sjos.12225 |
Ejemplares similares
-
Using linear increment models for the imputation of missing composite outcomes in randomized trials
por: O’Keeffe, Aidan G, et al.
Publicado: (2011) -
Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
por: Seaman, Shaun R, et al.
Publicado: (2012) -
Missing at random: a stochastic process perspective
por: Farewell, D. M., et al.
Publicado: (2022) -
A dynamic approach for reconstructing missing longitudinal data using the
linear increments model
por: Aalen, Odd O., et al.
Publicado: (2010) -
Semi-Parametric Methods of Handling Missing Data in Mortal Cohorts
under Non-Ignorable Missingness
por: Wen, Lan, et al.
Publicado: (2018)