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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.
Article in Chinese | WPRIM | ID: wpr-348821
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>
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Bias / Mortality / Models, Statistical / Heart Failure Type of study: Prognostic study / Risk factors Limits: Humans Language: Chinese Journal: Chinese Journal of Epidemiology Year: 2003 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Bias / Mortality / Models, Statistical / Heart Failure Type of study: Prognostic study / Risk factors Limits: Humans Language: Chinese Journal: Chinese Journal of Epidemiology Year: 2003 Type: Article