title: [An effective method to reduce bias between two compared groups: propensity score].
abstract: OBJECTIVE
  Through introduction of principal theory and algorithm of propensity score to design SAS macro programs for binary data.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Molecular Virology, Medical Center of Fudan University, Shanghai 200032, China.
authors.forename: Shou-jun
authors.initials: SJ
authors.lastname: Zhao
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhang
authors.forename: Xuan-yi
authors.initials: XY
authors.lastname: Wang
authors.forename: Yan-ning
authors.initials: YN
authors.lastname: Gao
mesh_terms: D000465:Algorithms; D015982:Bias; D006333:Heart Failure / Q000401:mortality*; D006801:Humans; D015233:Models, Statistical