A nonparametric multiple imputation approach for missing categorical data

BACKGROUND: Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness) probabilities. METHODS: We propose a nearest-neighbour multiple imputation approac...

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Detalles Bibliográficos
Autores principales: Zhou, Muhan, He, Yulei, Yu, Mandi, Hsu, Chiu-Hsieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461637/
https://www.ncbi.nlm.nih.gov/pubmed/28587662
http://dx.doi.org/10.1186/s12874-017-0360-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5461637/
https://www.ncbi.nlm.nih.gov/pubmed/28587662
http://dx.doi.org/10.1186/s12874-017-0360-2

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