Propensity Score Techniques and the Assessment of Measured Covariate Balance to Test Causal Associations in Psychological Research

被引:600
作者
Harder, Valerie S. [1 ]
Stuart, Elizabeth A. [2 ,3 ]
Anthony, James C. [4 ]
机构
[1] Univ Vermont, Coll Med, Dept Psychiat, Burlington, VT 05401 USA
[2] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Mental Hlth, Baltimore, MD USA
[3] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Biostat, Baltimore, MD USA
[4] Michigan State Univ, Coll Human Med, Dept Epidemiol, E Lansing, MI 48824 USA
关键词
observational studies; causal inference; standardized bias; cannabis; INFERENCE; BIAS; SUBCLASSIFICATION; SENSITIVITY; ADJUSTMENT; REGRESSION; MODELS;
D O I
10.1037/a0019623
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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.
引用
收藏
页码:234 / 249
页数:16
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