Comparison of Methods for Handling Missing Covariate Data

Missing covariate data is a common problem in nonlinear mixed effects modelling of clinical data. The aim of this study was to implement and compare methods for handling missing covariate data in nonlinear mixed effects modelling under different missing data mechanisms. Simulations generated data fo...

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Detalles Bibliográficos
Autores principales: Johansson, Åsa M., Karlsson, Mats O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3787222/
https://www.ncbi.nlm.nih.gov/pubmed/24022319
http://dx.doi.org/10.1208/s12248-013-9526-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3787222/
https://www.ncbi.nlm.nih.gov/pubmed/24022319
http://dx.doi.org/10.1208/s12248-013-9526-y

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