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Pattern Recognition of Longitudinal Trial Data with Nonignorable Missingness: An Empirical Case Study

Methods for identifying meaningful growth patterns of longitudinal trial data with both nonignorable intermittent and drop-out missingness are rare. In this study, a combined approach with statistical and data mining techniques is utilized to address the nonignorable missing data issue in growth pat...

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Detalhes bibliográficos
Main Authors: Fang, Hua, Espy, Kimberly Andrews, Rizzo, Maria L., Stopp, Christian, Wiebe, Sandra A., Stroup, Walter W.
Formato: Artigo
Idioma:Inglês
Publicado em: 2009
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC2844665/
https://ncbi.nlm.nih.gov/pubmed/20336179
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1142/S0219622009003508
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