2021/05/06 by Stephen Chaudoin, Brian J. Gaines, Avital Livny · 46 citations
Mathematics · Psychology · Social Sciences · #Advanced Causal Inference Techniques #Affect (linguistics) #Causal inference #Causal model #Computer science #Econometrics #Economics #Mathematics #Mediation #Microeconomics #Order (exchange) #Outcome (game theory) #Political science #Psychology #Set (abstract data type) #Social Capital and Networks #Social psychology #Statistics #Survey Methodology and Nonresponse
paper · doi:10.1086/715166
published in The Journal of Politics 83(4), 1851-1856 (University of Chicago Press)
openalex publication_date 2021/05/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25
Causal mediation analysis requires measurement of an outcome variable (O) with and without treatment, plus a set of mediator variables (M) that constitute possible pathways for the treatment effect. There is no consensus on whether surveys should measure potentially mediating variables before or after the outcome variables—MO or OM. We use a replication exercise to demonstrate how the order of mediator and outcome items can be consequential for the results from causal mediation analysis. Order can affect mediation conclusions, even if the treatment effect is similar across designs. As such, randomizing order is usually prudent, although best practice depends on the researcher’s contextual knowledge about her particular application.