Generalized Inference for Mediation Analysis

Xiaoyang Ma, David P. MacKinnon, T Mathew, Brian Agan, George Luta () and Ionut Bebu
Additional contact information
Xiaoyang Ma: Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC 20007, USA
David P. MacKinnon: Department of Psychology, Arizona State University, Tempe, AZ 85281, USA
Brian Agan: Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
George Luta: Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC 20007, USA
Ionut Bebu: Department of Biostatistics and Bioinformatics, George Washington University, Rockville, MD 20852, USA

Mathematics, 2025, vol. 13, issue 3, 1-13

Abstract: Mediation analysis has a long history and its use in applied research has been increasing. Studying mediators can help improve our understanding of mechanisms relating independent and dependent variables. The objective of this paper is to compare different methods to construct confidence intervals for the mediation effect for the one-mediator and two-mediator models. For the one-mediator model, we evaluated the generalized pivotal quantity (GPQ) method, the PRODCLIN method, bootstrap methods, the Sobel method, the Goodman method, and the Monte Carlo method. For the two-mediator model, we evaluated a new GPQ method, bootstrap methods, the Sobel method, the Goodman method, and the Monte Carlo method. Simulation studies compared the performance of the methods for sample sizes of 50, 100, and 200. The results of the simulation studies indicated that, for the simple traditional mediation models under consideration, the GPQ method performed well when compared with the other methods. Future work should consider the extension of the GPQ method to causal mediation analysis involving more complex models with multiple mediators.

Keywords: mediation analysis; GPQ method; Monte Carlo method (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/3/396/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/3/396/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:3:p:396-:d:1576815

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().