Evidence map›Paper›PMID 42215736›Full record

ArticleBehavior research methods2026

Synthesis of single-case design mediation effects using two-stage multilevel modeling.

Mariola Moeyaert, Milica Miočević, Yaosheng Lou, Matthew J Valente

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In one paragraph

Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mariola MoeyaertDepartment of Educational and Counseling Psychology, University at Albany, the State University of New York, 1400 Washington Ave, Albany, NY, 12222, USA. mmoeyaert@albany.edu.
Milica MiočevićDepartment of Psychology, McGill University, Montreal, QC, Canada.
Yaosheng LouDepartment of Educational and Counseling Psychology, University at Albany, the State University of New York, 1400 Washington Ave, Albany, NY, 12222, USA.
Matthew J ValenteDepartment of Biostatistics and Data Science, University of South Florida, Tampa, FL, USA.

Funding

Institute of Education Sciences R305D240044
6 · The paper itself

Abstract

Mediation analysis in single-case experimental designs (SCEDs) allows for evaluating mechanisms through which interventions achieve effects for a single individual. Modeling approaches have been described and empirically validated for mediation analysis in the AB phase design (i.e., SCED involving only one participant with one baseline and one intervention condition). However, no study to date has focused on synthesizing indirect effects across participants from a multiple-baseline design (MBD). The current study fills this gap by investigating the performance of the two-stage multilevel modeling approach to synthesize indirect effects using a large-scale Monte Carlo simulation study. An empirical demonstration with interpretation of results is provided. The results are promising for estimation of the indirect effect, as unbiased effects are obtained under all conditions that have more than three participants. If statistical inference is of interest, then the approach can be recommended for at least 20 study participants and a nonzero value for the mediator-outcome relation. Under these conditions, the coverage proportion is close to the nominal level of .95, and the Type I error rate is controlled. To obtain sufficient power to identify a true indirect effect, at least eight participants, a low between-case variance in mediator-outcome relation, and a mediator-outcome relation of 0.39 or higher are needed.

Indexed as

Mediation AnalysisModels, StatisticalMultilevel AnalysisResearch DesignSingle-Case Studies as TopicComputer SimulationHumansMonte Carlo MethodMediation analysisSingle-case experimental designTwo-stage multilevel modeling

Identifiers

PMID42215736

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.