title: Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research.
abstract: There is considerable interest in using propensity score (PS) statistical techniques to address questions of causal inference in psychological research. Many PS techniques exist, yet few guidelines are available to aid applied researchers in their understanding, use, and evaluation. In this study, the authors give an overview of available techniques for PS estimation and PS application. They also provide a way to help compare PS techniques, using the resulting measured covariate balance as the criterion for selecting between techniques. The empirical example for this study involves the potential causal relationship linking early-onset cannabis problems and subsequent negative mental health outcomes and uses data from a prospective cohort study. PS techniques are described and evaluated on the basis of their ability to balance the distributions of measured potentially confounding covariates for individuals with and without early-onset cannabis problems. This article identifies the PS techniques that yield good statistical balance of the chosen measured covariates within the context of this particular research question and cohort.
authors.affiliation: Department of Psychiatry, University of Vermont, 1 South Prospect Street, Burlington, VT 05401, USA. vharder@uvm.edu
authors.forename: Valerie S
authors.initials: VS
authors.lastname: Harder
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Stuart
authors.forename: James C
authors.initials: JC
authors.lastname: Anthony
mesh_terms: D000293:Adolescent; D035841:Behavioral Research / Q000379:methods* / Q000706:statistics & numerical data; D015982:Bias; D015984:Causality; D002648:Child; D006801:Humans; D002189:Marijuana Abuse / Q000517:prevention & control / Q000523:psychology; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods / Q000706:statistics & numerical data; D057216:Propensity Score; D012044:Regression Analysis; D012984:Software
references.citation: Annu Rev Psychol. 2009;60:549-76
references.pmid: 18652544
references.citation: Am J Epidemiol. 2006 Feb 1;163(3):262-70
references.pmid: 16371515
references.citation: Psychol Methods. 2007 Sep;12(3):247-67
references.pmid: 17784793
references.citation: Am J Epidemiol. 2008 Sep 15;168(6):592-601
references.pmid: 18687663
references.citation: Suicide Life Threat Behav. 2004 Winter;34(4):395-407
references.pmid: 15585461
references.citation: Stat Sci. 2010 Feb 1;25(1):1-21
references.pmid: 20871802
references.citation: Dev Psychol. 2008 Mar;44(2):395-406
references.pmid: 18331131
references.citation: Biometrics. 1996 Mar;52(1):249-64
references.pmid: 8934595
references.citation: Arch Gen Psychiatry. 2007 Dec;64(12):1435-42
references.pmid: 18056552
references.citation: Stat Med. 2004 Oct 15;23(19):2937-60
references.pmid: 15351954
references.citation: Annu Rev Psychol. 2000;51:345-75
references.pmid: 10751975
references.citation: Am J Epidemiol. 2006 Mar 1;163(5):404-11
references.pmid: 16421241
references.citation: Pharmacoepidemiol Drug Saf. 2004 Dec;13(12):855-7
references.pmid: 15386710
references.citation: Biometrics. 1991 Mar;47(1):87-100
references.pmid: 2049516
references.citation: Stat Med. 2009 Apr 30;28(9):1402-14
references.pmid: 19222021
references.citation: Epidemiology. 2000 Sep;11(5):550-60
references.pmid: 10955408
references.citation: Psychol Methods. 2008 Dec;13(4):279-313
references.pmid: 19071996
references.citation: Am J Community Psychol. 1991 Aug;19(4):563-84
references.pmid: 1755436
references.citation: Am J Public Health. 1998 Oct;88(10):1490-5
references.pmid: 9772850
references.citation: Psychol Methods. 2004 Dec;9(4):403-25
references.pmid: 15598095
references.citation: Biometrics. 1968 Jun;24(2):295-313
references.pmid: 5683871