Mariola Moeyaert

2.7k total citations
93 papers, 1.9k citations indexed

About

Mariola Moeyaert is a scholar working on Developmental and Educational Psychology, Management Science and Operations Research and Cognitive Neuroscience. According to data from OpenAlex, Mariola Moeyaert has authored 93 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Developmental and Educational Psychology, 25 papers in Management Science and Operations Research and 21 papers in Cognitive Neuroscience. Recurrent topics in Mariola Moeyaert's work include Behavioral and Psychological Studies (57 papers), Optimal Experimental Design Methods (24 papers) and Autism Spectrum Disorder Research (20 papers). Mariola Moeyaert is often cited by papers focused on Behavioral and Psychological Studies (57 papers), Optimal Experimental Design Methods (24 papers) and Autism Spectrum Disorder Research (20 papers). Mariola Moeyaert collaborates with scholars based in United States, Belgium and Netherlands. Mariola Moeyaert's co-authors include Wim Van Den Noortgate, John M. Ferron, S. Natasha Beretvas, Maaike Ugille, Rumen Manolov, Iryna Babik, Andréa Baraldi Cunha, Michele A. Lobo, Patrick Onghena and Rommel Bunuan and has published in prestigious journals such as Psychological Bulletin, SHILAP Revista de lepidopterología and Computers in Human Behavior.

In The Last Decade

Mariola Moeyaert

82 papers receiving 1.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mariola Moeyaert United States 25 1.1k 560 357 325 288 93 1.9k
Rumen Manolov Spain 21 748 0.7× 402 0.7× 215 0.6× 231 0.7× 178 0.6× 80 1.2k
John H. Hitchcock United States 19 1.7k 1.5× 1.1k 2.0× 243 0.7× 801 2.5× 284 1.0× 63 2.9k
Daniel M. Maggin United States 28 1.7k 1.5× 914 1.6× 127 0.4× 855 2.6× 191 0.7× 74 2.4k
Marilyn S. Thompson United States 24 585 0.5× 311 0.6× 174 0.5× 724 2.2× 126 0.4× 77 2.2k
Stefan C. Dombrowski United States 26 598 0.5× 156 0.3× 469 1.3× 403 1.2× 159 0.6× 78 1.7k
Rob Horner United States 11 1.2k 1.1× 853 1.5× 74 0.2× 665 2.0× 128 0.4× 22 1.8k
Shanna Hagan–Burke United States 21 1.1k 1.0× 541 1.0× 63 0.2× 443 1.4× 247 0.9× 47 1.6k
John L. Davis United States 22 1.8k 1.6× 1.5k 2.7× 108 0.3× 1.1k 3.3× 328 1.1× 74 3.1k
Matthew R. Reynolds United States 26 791 0.7× 230 0.4× 332 0.9× 230 0.7× 349 1.2× 58 1.9k
Gary L. Canivez United States 34 1.0k 0.9× 266 0.5× 793 2.2× 716 2.2× 308 1.1× 104 2.7k

Countries citing papers authored by Mariola Moeyaert

Since Specialization
Citations

This map shows the geographic impact of Mariola Moeyaert's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mariola Moeyaert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mariola Moeyaert more than expected).

Fields of papers citing papers by Mariola Moeyaert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mariola Moeyaert. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mariola Moeyaert. The network helps show where Mariola Moeyaert may publish in the future.

Co-authorship network of co-authors of Mariola Moeyaert

This figure shows the co-authorship network connecting the top 25 collaborators of Mariola Moeyaert. A scholar is included among the top collaborators of Mariola Moeyaert based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mariola Moeyaert. Mariola Moeyaert is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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James, Drexler, A. Bowling, & Mariola Moeyaert. (2025). Essentialism and Ethnoracial Bias: A Meta-Analysis. Review of General Psychology. 30(1). 53–103.
3.
Chen, Quan, Zheng Yan, Mariola Moeyaert, & Robert L. Bangert‐Drowns. (2024). Mobile multitasking in learning: A meta-analysis of effects of mobilephone distraction on young adults’ immediate recall. Computers in Human Behavior. 162. 108432–108432. 4 indexed citations
4.
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Moeyaert, Mariola, et al.. (2024). The effect of eye movement desensitization and reprocessing on fibromyalgia: A multiple-baseline experimental case study across ten participants. Neuropsychological Rehabilitation. 34(10). 1422–1454. 5 indexed citations
6.
Moeyaert, Mariola, et al.. (2023). Single-case design meta-analyses in education and psychology: a systematic review of methodology. SHILAP Revista de lepidopterología. 8. 1190362–1190362. 3 indexed citations
7.
Moeyaert, Mariola, et al.. (2023). Outcomes of Warfarin Home INR Monitoring vs Office-Based Monitoring: a Retrospective Claims-Based Analysis. Journal of General Internal Medicine. 39(7). 1127–1134. 2 indexed citations
8.
Miočević, Milica, Mariola Moeyaert, Axel Mayer, & Amanda Kay Montoya. (2022). Causal Mediation Analysis in Single Case Experimental Designs: Introduction to the Special Issue. Evaluation & the Health Professions. 45(1). 3–7. 6 indexed citations
9.
Epstein, Leonard H., Warren K. Bickel, Susan M. Czajkowski, et al.. (2021). Single case designs for early phase behavioral translational research in health psychology.. Health Psychology. 40(12). 858–874. 6 indexed citations
10.
Moeyaert, Mariola, et al.. (2021). The Power to Explain Variability in Intervention Effectiveness in Single-Case Research Using Hierarchical Linear Modeling. Perspectives on Behavior Science. 45(1). 13–35. 14 indexed citations
11.
Moeyaert, Mariola, et al.. (2020). Effect size estimation for combined single-case experimental designs. Evidence-Based Communication Assessment and Intervention. 14(1-2). 28–51. 12 indexed citations
12.
Moeyaert, Mariola, et al.. (2020). Single-Case Metric Ranking Tool. OSF Preprints (OSF Preprints). 2 indexed citations
13.
Declercq, Lies, Wilfried Cools, S. Natasha Beretvas, et al.. (2019). MultiSCED: A tool for (meta-)analyzing single-case experimental data with multilevel modeling. Behavior Research Methods. 52(1). 177–192. 31 indexed citations
14.
Ferron, John M., et al.. (2017). Approaches for Specifying the Level-1 Error Structure When Synthesizing Single-Case Data. The Journal of Experimental Education. 87(1). 55–74. 23 indexed citations
15.
Moeyaert, Mariola, David Rindskopf, Patrick Onghena, & Wim Van Den Noortgate. (2017). Multilevel modeling of single-case data: A comparison of maximum likelihood and Bayesian estimation.. Psychological Methods. 22(4). 760–778. 46 indexed citations
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Ferron, John M., Mariola Moeyaert, Wim Van Den Noortgate, & S. Natasha Beretvas. (2014). Estimating causal effects from multiple-baseline studies: Implications for design and analysis.. Psychological Methods. 19(4). 493–510. 56 indexed citations
18.
Moeyaert, Mariola, Maaike Ugille, John M. Ferron, S. Natasha Beretvas, & Wim Van Den Noortgate. (2013). The Three-Level Synthesis of Standardized Single-Subject Experimental Data: A Monte Carlo Simulation Study. Multivariate Behavioral Research. 48(5). 719–748. 61 indexed citations
19.
Moeyaert, Mariola, Maaike Ugille, John M. Ferron, S. Natasha Beretvas, & Wim Van Den Noortgate. (2012). Modeling external events in the three-level analysis of multiple-baseline across-participants designs: A simulation study. Behavior Research Methods. 45(2). 547–559. 22 indexed citations
20.
Ugille, Maaike, Mariola Moeyaert, S. Natasha Beretvas, John M. Ferron, & Wim Van Den Noortgate. (2012). Multilevel meta-analysis of single-subject experimental designs: A simulation study. Behavior Research Methods. 44(4). 1244–1254. 44 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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