An effective method to reduce bias between two compared groups: propensity score / 中华流行病学杂志
Chinese Journal of Epidemiology
; (12): 516-519, 2003.
Artigo
em Chinês
| WPRIM (Pacífico Ocidental)
| ID: wpr-348821
Biblioteca responsável:
WPRO
ABSTRACT
<p><b>OBJECTIVE</b>Through introduction of principal theory and algorithm of propensity score to design SAS macro programs for binary data.</p><p><b>METHODS</b>Propensity score method was used to compare the differences of character variables between two groups, and the association of DNR (Do Not Resuscitate) with the mortality of congestive heart failure was evaluated with different methods.</p><p><b>RESULTS</b>Significant differences among the character variables between two groups were effectively balanced with stratification or matching method. The odds ratios of DNR with the in-hospital mortality rate of congestive heart failure were estimated identical with different algorithms and to find that the association of DNR to in-hospital mortality was highly significant.</p><p><b>CONCLUSION</b>Propensity score was a good algorithm that could be used to analyze any kind of observational data for matching the effects among the character variables.</p>
Texto completo:
Disponível
Contexto em Saúde:
ODS3 - Saúde e Bem-Estar
/
ODS3 - Meta 3.4 Reduzir as mortes prematuras devido doenças não transmissíveis
Problema de saúde:
Meta 3.4: Reduzir as mortes prematuras devido doenças não transmissíveis
/
Doença Cardiovascular
/
Outras Doenças Circulatórias
Base de dados:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Viés
/
Mortalidade
/
Modelos Estatísticos
/
Insuficiência Cardíaca
Tipo de estudo:
Estudo prognóstico
/
Fatores de risco
Limite:
Humanos
Idioma:
Chinês
Revista:
Chinese Journal of Epidemiology
Ano de publicação:
2003
Tipo de documento:
Artigo