title: Squeezing the balloon: propensity scores and unmeasured covariate balance.
abstract: OBJECTIVE
  To assess the covariate balancing properties of propensity score-based algorithms in which covariates affecting treatment choice are both measured and unmeasured.
  
  
  METHODS
  A simulation model of treatment choice and outcome.
  
  
  METHODS
  Simulation.
  
  
  METHODS
  Eight simulation scenarios varied with the values placed on measured and unmeasured covariates and the strength of the relationships between the measured and unmeasured covariates. The balance of both measured and unmeasured covariates was compared across patients either grouped or reweighted by propensity scores methods.
  
  
  RESULTS
  Propensity score algorithms require unmeasured covariate variation that is unrelated to measured covariates, and they exacerbate the imbalance in this variation between treated and untreated patients relative to the full unweighted sample.
  
  
  CONCLUSIONS
  The balance of measured covariates between treated and untreated patients has opposite implications for unmeasured covariates in randomized and observational studies. Measured covariate balance between treated and untreated patients in randomized studies reinforces the notion that all covariates are balanced. In contrast, forced balance of measured covariates using propensity score methods in observational studies exacerbates the imbalance in the independent portion of the variation in the unmeasured covariates, which can be likened to squeezing a balloon. If the unmeasured covariates affecting treatment choice are confounders, propensity score methods can exacerbate the bias in treatment effect estimates.
authors.affiliation: College of Pharmacy and College of Public Health, University of Iowa, Iowa City, IA 52242, USA. john-brooks@uiowa.edu
authors.forename: John M
authors.initials: JM
authors.lastname: Brooks
authors.forename: Robert L
authors.initials: RL
authors.lastname: Ohsfeldt
mesh_terms: D006302:Health Services Research / Q000379:methods; D006801:Humans; D008962:Models, Theoretical; D010043:Outcome and Process Assessment, Health Care / Q000379:methods / Q000706:statistics & numerical data; D057216:Propensity Score; D016032:Randomized Controlled Trials as Topic / Q000379:methods