A flexible quantile regression model for medical costs with application to Medical Expenditure Panel Survey Study.
Stat Med
; 37(17): 2645-2666, 2018 07 30.
Article
em En
| MEDLINE
| ID: mdl-29722044
ABSTRACT
Medical costs are often skewed to the right and heteroscedastic, having a sophisticated relation with covariates. Mean function regression models with low-dimensional covariates have been extensively considered in the literature. However, it is important to develop a robust alternative to find the underlying relationship between medical costs and high-dimensional covariates. In this paper, we propose a new quantile regression model to analyze medical costs. We also consider variable selection, using an adaptive lasso penalized variable selection method to identify significant factors of the covariates. Simulation studies are conducted to illustrate the performance of the estimation method. We apply our method to the analysis of the Medical Expenditure Panel Survey dataset.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Análise de Regressão
/
Modelos Econométricos
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Custos e Análise de Custo
Tipo de estudo:
Diagnostic_studies
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Health_economic_evaluation
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Prognostic_studies
Limite:
Humans
País como assunto:
America do norte
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article