Reader reaction to "a robust method for estimating optimal treatment regimes" by Zhang et al. (2012).
Biometrics
; 71(1): 267-273, 2015 Mar.
Article
em En
| MEDLINE
| ID: mdl-25228049
ABSTRACT
A recent article (Zhang et al., 2012, Biometrics 168, 1010-1018) compares regression based and inverse probability based methods of estimating an optimal treatment regime and shows for a small number of covariates that inverse probability weighted methods are more robust to model misspecification than regression methods. We demonstrate that using models that fit the data better reduces the concern about non-robustness for the regression methods. We extend the simulation study of Zhang et al. (2012, Biometrics 168, 1010-1018), also considering the situation of a larger number of covariates, and show that incorporating random forests into both regression and inverse probability weighted based methods improves their properties.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
/
Ensaios Clínicos como Assunto
/
Modelos Estatísticos
/
Avaliação de Resultados em Cuidados de Saúde
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Sistemas de Apoio a Decisões Clínicas
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Female
/
Humans
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article