title: An empirical comparison of tree-based methods for propensity score estimation.
abstract: OBJECTIVE
  To illustrate the use of ensemble tree-based methods (random forest classification [RFC] and bagging) for propensity score estimation and to compare these methods with logistic regression, in the context of evaluating the effect of physical and occupational therapy on preschool motor ability among very low birth weight (VLBW) children.
  
  
  METHODS
  We used secondary data from the Early Childhood Longitudinal Study Birth Cohort (ECLS-B) between 2001 and 2006.
  
  
  METHODS
  We estimated the predicted probability of treatment using tree-based methods and logistic regression (LR). We then modeled the exposure-outcome relation using weighted LR models while considering covariate balance and precision for each propensity score estimation method.
  
  
  RESULTS
  Among approximately 500 VLBW children, therapy receipt was associated with moderately improved preschool motor ability. Overall, ensemble methods produced the best covariate balance (Mean Squared Difference: 0.03-0.07) and the most precise effect estimates compared to LR (Mean Squared Difference: 0.11). The overall magnitude of the effect estimates was similar between RFC and LR estimation methods.
  
  
  CONCLUSIONS
  Propensity score estimation using RFC and bagging produced better covariate balance with increased precision compared to LR. Ensemble methods are a useful alterative to logistic regression to control confounding in observational studies.
authors.affiliation: Center for Health Promotion and Disease Prevention, University of North Carolina at Chapel Hill, University of North Carolina, Chapel Hill, NC.
authors.forename: Stephanie
authors.initials: S
authors.lastname: Watkins
authors.forename: Michele
authors.initials: M
authors.lastname: Jonsson-Funk
authors.forename: M Alan
authors.initials: MA
authors.lastname: Brookhart
authors.forename: Steven A
authors.initials: SA
authors.lastname: Rosenberg
authors.forename: T Michael
authors.initials: TM
authors.lastname: O'Shea
authors.forename: Julie
authors.initials: J
authors.lastname: Daniels
mesh_terms: D002675:Child, Preschool; D019988:Children with Disabilities / Q000534:rehabilitation*; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D019102:Infant, Very Low Birth Weight; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D019957:Motor Skills Disorders / Q000534:rehabilitation*; D009788:Occupational Therapy; D026741:Physical Therapy Modalities; D057216:Propensity Score; D012107:Research Design; D016896:Treatment Outcome
keywords: Propensity scores; ensemble methods; tree-based methods