Causal Mediation Analysis in Single Case Experimental Designs: Introduction to the Special Issue

This special issue of Evaluation and the Health Professions is dedicated to methods for causal mediation analysis in Single Case Experimental Designs (SCEDs). Mediation analysis is used to identify intermediate variables that transmit the effect of the independent variable on the outcome. Until rece...

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Published inEvaluation & the health professions Vol. 45; no. 1; pp. 3 - 7
Main Authors Miočević, Milica, Moeyaert, Mariola, Mayer, Axel, Montoya, Amanda K.
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.03.2022
SAGE PUBLICATIONS, INC
Subjects
Between-subjects design
Clinical outcomes
Data analysis
Exceptions
Humans
Indirect effects
Longitudinal studies
Mediation Analysis
Medical diagnosis
Medical personnel
Medical research
Models, Statistical
Predictor Variables
Quantitative analysis
Research Design
Research Personnel
Special Issue: Single Subject Causal Mediation Analysis
Variables
special issue
mediation analysis
causal inference
SCEDs
introduction article
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Summary:This special issue of Evaluation and the Health Professions is dedicated to methods for causal mediation analysis in Single Case Experimental Designs (SCEDs). Mediation analysis is used to identify intermediate variables that transmit the effect of the independent variable on the outcome. Until recently, mediation analysis was mostly confined to between-subjects designs and panel studies with few exceptions. Consequently, most of the developments in causal mediation analysis have also been restricted to such designs. In applied health research, SCEDs have been used to evaluate total effects of treatments on outcomes of interest. Providing researchers with the methods for evaluating causal indirect effects for individual participants can lead to important improvements in diagnosis, treatment, and prevention. This special issue includes articles that describe advanced quantitative methods for testing mediators in SCEDs, propose and test approaches that allow for relaxing statistical assumptions that may not hold in real data, and illustrate mediation analysis for a single participant in real and simulated SCEDs data.
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ISSN:0163-2787
1552-3918
1552-3918
DOI:10.1177/01632787211073194