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ERIC Number: EJ933085
Record Type: Journal
Publication Date: 2011
Pages: 13
Abstractor: As Provided
Reference Count: 37
ISSN: ISSN-1070-5511
Estimating Causal Effects in Mediation Analysis Using Propensity Scores
Coffman, Donna L.
Structural Equation Modeling: A Multidisciplinary Journal, v18 n3 p357-369 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly assigned to levels of "M" but generally random assignment is not possible. We propose the use of propensity scores to help remove the selection bias that can result when individuals are not randomly assigned to levels of "M". The propensity score is the probability that an individual receives a particular level of "M". Results from a simulation study are presented to demonstrate this approach, referred to as Classical + Propensity Model (C+PM), confirming that the population parameters are recovered and that selection bias is successfully dealt with. Comparisons are made to the classical approach that does not include propensity scores. Propensity scores were estimated by a logistic regression model. If all confounders are included in the propensity model, then the C+PM is unbiased. If some, but not all, of the confounders are included in the propensity model, then the C+PM estimates are biased although not as severely as the classical approach (i.e., no propensity model is included). (Contains 3 figures and 5 tables.)
Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: Researchers
Language: English
Sponsor: N/A
Authoring Institution: N/A