How to deal with missing longitudinal data in cost of illness analysis in Alzheimer’s disease—suggestions from the GERAS observational study

BACKGROUND: Missing data are a common problem in prospective studies with a long follow-up, and the volume, pattern and reasons for missing data may be relevant when estimating the cost of illness. We aimed to evaluate the effects of different methods for dealing with missing longitudinal cost data...

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Detalles Bibliográficos
Autores principales: Belger, Mark, Haro, Josep Maria, Reed, Catherine, Happich, Michael, Kahle-Wrobleski, Kristin, Argimon, Josep Maria, Bruno, Giuseppe, Dodel, Richard, Jones, Roy W, Vellas, Bruno, Wimo, Anders
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4950752/
https://www.ncbi.nlm.nih.gov/pubmed/27430559
http://dx.doi.org/10.1186/s12874-016-0188-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4950752/
https://www.ncbi.nlm.nih.gov/pubmed/27430559
http://dx.doi.org/10.1186/s12874-016-0188-1

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