title: Bias due to sample selection in propensity score matching for a supportive housing program evaluation in New York City.
abstract: OBJECTIVE
  Little is known about influences of sample selection on estimation in propensity score matching. The purpose of the study was to assess potential selection bias using one-to-one greedy matching versus optimal full matching as part of an evaluation of supportive housing in New York City (NYC).
  
  
  METHODS
  Data came from administrative data for 2 groups of applicants who were eligible for an NYC supportive housing program in 2007-09, including chronically homeless adults with a substance use disorder and young adults aging out of foster care. We evaluated the 2 matching methods in their ability to balance covariates and represent the original population, and in how those methods affected outcomes related to Medicaid expenditures.
  
  
  RESULTS
  In the population with a substance use disorder, only optimal full matching performed well in balancing covariates, whereas both methods created representative populations. In the young adult population, both methods balanced covariates effectively, but only optimal full matching created representative populations. In the young adult population, the impact of the program on Medicaid expenditures was attenuated when one-to-one greedy matching was used, compared with optimal full matching.
  
  
  CONCLUSIONS
  Given covariate balancing with both methods, attenuated program impacts in the young adult population indicated that one-to-one greedy matching introduced selection bias.
authors.affiliation: Bureau of Epidemiology Services, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, New York, United States of America.
authors.forename: Sungwoo
authors.initials: S
authors.lastname: Lim
authors.affiliation: Department of Psychiatry and Biostatistics, Columbia University, New York, New York, United States of America.
authors.forename: Sue M
authors.initials: SM
authors.lastname: Marcus
authors.affiliation: Bureau of Epidemiology Services, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, New York, United States of America.
authors.forename: Tejinder P
authors.initials: TP
authors.lastname: Singh
authors.affiliation: Bureau of Epidemiology Services, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, New York, United States of America.
authors.forename: Tiffany G
authors.initials: TG
authors.lastname: Harris
authors.affiliation: Bureau of Epidemiology Services, Division of Epidemiology, New York City Department of Health and Mental Hygiene, New York, New York, United States of America.
authors.forename: Amber
authors.initials: A
authors.lastname: Levanon Seligson
mesh_terms: D000328:Adult; D006703:Ill-Housed Persons; D006801:Humans; D009519:New York City; D015397:Program Evaluation / Q000706:statistics & numerical data*; D057216:Propensity Score; D011638:Public Housing / Q000706:statistics & numerical data*; D012107:Research Design; D015983:Selection Bias; D055815:Young Adult