Analysis of self-report and biochemically verified tobacco abstinence outcomes with missing data: a sensitivity analysis using two-stage imputation

BACKGROUND: Missing data are common in tobacco studies. It is well known that from the observed data alone, it is impossible to distinguish between missing mechanisms such as missing at random (MAR) and missing not at random (MNAR). In this paper, we propose a sensitivity analysis method to accommod...

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Detalles Bibliográficos
Autores principales: Zhang, Yiwen, Luo, Xianghua, Le, Chap T., Ahluwalia, Jasjit S., Thomas, Janet L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6299502/
https://www.ncbi.nlm.nih.gov/pubmed/30563473
http://dx.doi.org/10.1186/s12874-018-0635-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6299502/
https://www.ncbi.nlm.nih.gov/pubmed/30563473
http://dx.doi.org/10.1186/s12874-018-0635-2

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