Model validation and selection for personalized medicine using dynamic-weighted ordinary least squares.
Stat Methods Med Res
; 26(4): 1641-1653, 2017 Aug.
Article
em En
| MEDLINE
| ID: mdl-28486872
ABSTRACT
Model assessment is a standard component of statistical analysis, but it has received relatively little attention within the dynamic treatment regime literature. In this paper, we focus on the dynamic-weighted ordinary least squares approach to optimal dynamic treatment regime estimation, introducing how its double-robustness property may be leveraged for model assessment, and how quasilikelihood may be used for model selection. These ideas are demonstrated through simulation studies, as well as through application to data from the sequenced treatment alternatives to relieve depression study.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Análise dos Mínimos Quadrados
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Modelos Estatísticos
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Depressão
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Medicina de Precisão
Tipo de estudo:
Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article