The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Fitting three-level meta-analytic models in R: A step-by-step tutorial
Open accessAbstract
Applying a multilevel approach to meta-analysis is a strong method for dealing with dependency of effect sizes.However, this method is relatively unknown among researchers and, to date, has not been widely used in meta-analytic research.Therefore, the purpose of this tutorial was to show how a three-level random effects model can be applied to meta-analytic models in R using the rma.mv function of the metafor package.This application is illustrated by taking the reader through a step-by-step guide to the multilevel analyses comprising the steps of (1) organizing a data file; (2) setting up the R environment; (3) calculating an overall effect; (4) examining heterogeneity of within-study variance and between-study variance; (5) performing categorical and continuous moderator analyses; and (6) examining a multiple moderator model.By example, the authors demonstrate how the multilevel approach can be applied to meta-analytically examining the association between mental health disorders of juveniles and juvenile offender recidivism.In our opinion, the rma.mv function of the metafor package provides an easy and flexible way of applying a multi-level structure to meta-analytic models in R. Further, the multilevel meta-analytic models can be easily extended so that the potential moderating influence of variables can be examined.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“As a result, there no information is lost and (moderator) effects can be estimated more precisely and with maximum power in the statistical analyses (Assink and Wibbelink 2016).”
From Risk Factors for School Absenteeism and Dropout: A Meta-Analytic Review (2019) · cites this paper as Assink and Wibbelink 2016
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“As recommended by Assink and Wibbelink (2016), moderation analyses should be conducted if less than 75% of the variance can be attributed to Level 1.”
From Therapeutic games to reduce anxiety and depression in young people: A systematic review and exploratory meta‐analysis of their use and effectiveness. (2024) · cites this paper as Assink and Wibbelink (2016)
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“There is no need to know the correlations between outcomes extracted from one study for estimating the covariance matrix of the effect sizes since the second level in the model accounts for sampling covariation ( Assink and Wibbelink, 2016 ).”
From The effect of contextual interference on transfer in motor learning - a systematic review and meta-analysis (2024) · cites this paper as Assink and Wibbelink, 2016
The cited source says what the claim attributes to it.
In the citing paper
“To deal with this intra-study dependency of prevalence estimates, we opted for the three-level model with random effects for data points obtained within one article to calculate pooled prevalence estimates (29, 30).”
From The global prevalence of autism spectrum disorder: A three-level meta-analysis (2023) · cites this paper as [30]
The cited source says what the claim attributes to it.
In the citing paper
“we used a multilevel approach to metaanalysis (Assink & Wibbelink, 2016), which is a strong method for dealing with dependency of effect sizes, as it accounts for the hierarchical structure of the data in which effect sizes are nested within studies (Van Den Noortgate & Onghena, 2003).”
From Associations between rejection sensitivity and mental health outcomes: A meta-analytic review (2017) · cites this paper as Assink & Wibbelink, 2016
The cited source says what the claim attributes to it.
In the citing paper
“The Knapp and Hartung method (2003) has the advantage that it reduces Type I‐errors (Assink & Wibbelink, 2016).”
From Does Natural Mentoring Matter? A Multilevel Meta‐analysis on the Association Between Natural Mentoring and Youth Outcomes (2018) · cites this paper as Assink & Wibbelink, 2016
The cited source says what the claim attributes to it.
In the citing paper
“A three‐level random effects model was used to account for three levels of variance, including the sampling variance of each effect size (level 1), the variance between effect sizes extracted from the same study (level 2), and the variance between the studies (level 3).”
From Does Natural Mentoring Matter? A Multilevel Meta‐analysis on the Association Between Natural Mentoring and Youth Outcomes (2018) · cites this paper as Assink & Wibbelink, 2016
The cited source says what the claim attributes to it.
In the citing paper
“Likelihood‐ratio tests were used to compare the deviance scores of the full model to the deviance of models excluding level 2 or level 3 variance parameters, making it possible to determine whether significant variance is present at the two levels (Assink & Wibbelink, 2016).”
From Does Natural Mentoring Matter? A Multilevel Meta‐analysis on the Association Between Natural Mentoring and Youth Outcomes (2018) · cites this paper as Assink & Wibbelink, 2016
The cited source says what the claim attributes to it.
In the citing paper
“This analysis considers three levels of variance components distributed across the model, including variance between effect sizes from the same study and variance between studies; this therefore allows for an examination of how effect sizes vary between participants (Level 1), outcomes (Level 2) and studies (Level 3; Assink & Wibbelink, 2016).”
From Therapeutic games to reduce anxiety and depression in young people: A systematic review and exploratory meta‐analysis of their use and effectiveness. (2024) · cites this paper as Assink & Wibbelink, 2016
The cited source says what the claim attributes to it.
In the citing paper
“The analyses suggested that there was significant variability ( p = .001) between effect sizes (Level 2) and between studies (Level 3), indicating that moderator analyses should be conducted (Assink & Wibbelink, 2016).”
From Therapeutic games to reduce anxiety and depression in young people: A systematic review and exploratory meta‐analysis of their use and effectiveness. (2024) · cites this paper as Assink & Wibbelink, 2016
The cited source says what the claim attributes to it.
In the citing paper
“Dependency of effect sizes normally means that effect sizes within studies are correlated (as these are expected to show a certain similarity); this creates an overlap of information and inflates information produced by the analysis, which can result in an overconfidence in its results (Assink & Wibbelink, 2016).”
From Therapeutic games to reduce anxiety and depression in young people: A systematic review and exploratory meta‐analysis of their use and effectiveness. (2024) · cites this paper as Assink & Wibbelink, 2016
In the citing paper
“A hierarchical multi-level multivariate meta-analytical approach for data plotting was used to account for statistical dependence in effect sizes from multiple within-study comparison arms (cannabis use frequencies) to a common control group (non-use)”
From Risk-thresholds for the association between frequency of cannabis use and the development of psychosis: a systematic review and meta-analysis (2023) · cites this paper as Assink & Wibbelink, 2016
In the citing paper
“As studies reported more than one effect size (for example, depression and suicidal ideation), we opted for a multilevel meta-analysis with three levels (for example, ref. 47), a random-effect model, which enables modelling the dependent effect sizes from the same study.”
From Prevalence and severity of mental health problems in early-career researchers: a systematic review and meta-analysis (2026) · cites this paper as [47]
In the citing paper
“For parameter estimation, restricted maximum likelihood estimation was applied, and for standard errors, P values and 95% CIs, Knapp and Hartung’s adjustment47,227 was used.”
From Prevalence and severity of mental health problems in early-career researchers: a systematic review and meta-analysis (2026) · cites this paper as [47]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722
Operating characteristics of a rank correlation test for publication bias
Begg, C. B., & Mazumdar, M. (1994) · Biometrics · doi:10.2307/2533446 · Cited by 16,955
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009) · doi:10.1002/9780470743386 · Cited by 14,225
Duval, S., & Tweedie, R. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.00455.x · Cited by 14,099
Wasserman, S. S., Hedges, L. V., & Olkin, I. (1988) · Journal of Educational Statistics · doi:10.2307/1164953 · Cited by 10,377
(2007) · Cited by 10,092
(2000) · Cited by 9,198
The file drawer problem and tolerance for null results.
Rosenthal, R. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.3.638 · Cited by 9,068
Research works printed but not linked: 1
- Egger, M. and Davey-Smith, G. and Altman, D., 2001, Systematic Reviews in Healthcare
Cited by
Sorted by citations
Items 201–300 of 1,003
Anacleto, T. M., Kozlowsky‐Suzuki, B., Björn, A. V., Yekta, S. S., Masuda, L. S. M., de Oliveira, V. P., & Enrich‐Prast, A. (2024) · Scientific Reports · doi:10.1038/s41598-024-51603-9 · Cited by 53
Identifying Key Antecedents of Quiet Quitting Among Nurses: A Cross‐Profession Meta‐Analytic Review
Geng, R., Geng, X., & Geng, S. (2025) · Journal of Advanced Nursing · doi:10.1111/jan.16934 · Cited by 63
The effectiveness of pre-performance routines in sports: a meta-analysis
Rupprecht, A. G. O., Tran, U. S., & Gröpel, P. (2021) · International Review of Sport and Exercise Psychology · doi:10.1080/1750984x.2021.1944271 · Cited by 68
Barhorst, E. E., Boruch, A. E., Cook, D. B., & Lindheimer, J. B. (2021) · Pain Medicine · doi:10.1093/pm/pnab308 · Cited by 54
Feter, N., Ligeza, T. S., Bashir, N., Shanmugam, R., Herrera, B. M., Aldabbagh, T., Usman, A.-F., Yonezawa, A., McCarthy, S., Herrera, D., et al. (2024) · British Journal of Sports Medicine · doi:10.1136/bjsports-2024-108444 · Cited by 49
Effectiveness of climate change education—a meta-analysis
Aeschbach, V. M.-J., Schwichow, M., & Rieß, W. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1563816 · Cited by 75
A meta‐analysis of the effect of values affirmation on academic achievement
Wu, Z., Spreckelsen, T. F., & Cohen, G. L. (2021) · Journal of Social Issues · doi:10.1111/josi.12415 · Cited by 67
Yang, Y., Macleod, M. R., Pan, J., Lagisz, M., & Nakagawa, S. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.105016 · Cited by 53
The effect of self-confidence on performance in sports: a meta-analysis and narrative review
Jekauc, D., Fiedler, J., Wunsch, K., Mülberger, L., Burkart, D., Kilgus, A., & Fritsch, J. (2023) · International Review of Sport and Exercise Psychology · doi:10.1080/1750984x.2023.2222376 · Cited by 76
Gutterswijk, R. V., Kuiper, C. H. Z., Lautan, N., Kunst, E. G., van der Horst, F. C. P., Stams, G. J. J. M., & Prinzie, P. (2020) · Children and Youth Services Review · doi:10.1016/j.childyouth.2020.104950 · Cited by 56
Youth Initiated Mentoring: A Meta-analytic Study of a Hybrid Approach to Youth Mentoring
van Dam, L., Blom, D., Kara, E., Assink, M., Stams, G. J. J. M., Schwartz, S. E. O., & Rhodes, J. E. (2020) · Journal of Youth and Adolescence · doi:10.1007/s10964-020-01336-5 · Cited by 56
Self-citationRacey, M., Ali, M. U., Sherifali, D., Fitzpatrick‐Lewis, D., Lewis, R., Jovkovic, M., Gramlich, L. M., Keller, H., Holroyd-Leduc, J. M., Giguere, A. M. C., et al. (2021) · CMAJ Open · doi:10.9778/cmajo.20200248 · Cited by 47
How does interpreting experience enhance working memory and short-term memory: A meta-analysis
Wen, H., & Dong, Y. (2019) · Journal of Cognitive Psychology · doi:10.1080/20445911.2019.1674857 · Cited by 57
Steur, G., Verburg, R. W., Wassen, M. J., & Verweij, P. A. (2020) · Ecosystem Services · doi:10.1016/j.ecoser.2020.101107 · Cited by 49
Divergent Thinking and Evaluative Skill: A Meta‐Analysis
Guo, Y., Lin, S., Acar, S., Jin, S., Xu, X., Ye, F., & Zeng, Y. (2022) · The Journal of Creative Behavior · doi:10.1002/jocb.539 · Cited by 47
Conley, C. S., Raposa, E. B., Bartolotta, K., Broner, S. E., Hareli, M., Forbes, N., Christensen, K. M., & Assink, M. (2022) · JMIR Mental Health · doi:10.2196/34254 · Cited by 53
Self-citationBeamish, N., Davenport, M. H., Ali, M. U., Gervais, M. J., Sjwed, T. N., Bains, G., Sivak, A., Deering, R. E., & Ruchat, S.-M. (2024) · British Journal of Sports Medicine · doi:10.1136/bjsports-2024-108619 · Cited by 46
Dudek, E. M., & Dodell‐Feder, D. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.12.020 · Cited by 45
Singh, B., Mellinger, C., Earls, H. A., Tran, J., Bardsley, B., & Correll, J. (2021) · Personality and Social Psychology Bulletin · doi:10.1177/01461672211024463 · Cited by 46
Khoury, J. E., Giles, L., Kaur, H., Johnson, D., González, A., & Atkinson, L. R. (2022) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2022.105969 · Cited by 51
Weisz, J. R., Venturo‐Conerly, K. E., Fitzpatrick, O. M., Frederick, J., & Ng, M. Y. (2023) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-080921-082920 · Cited by 52
Abd-Alrazaq, A. A., Alajlani, M., Ahmad, R., AlSaad, R., Aziz, S., Ahmed, A., Alsahli, M. A., Damseh, R., & Sheikh, J. I. (2023) · Journal of Medical Internet Research · doi:10.2196/52622 · Cited by 62
Llanos-Lagos, C., Ramírez‐Campillo, R., Moran, J., & de Villarreal, E. S. (2024) · Sports Medicine · doi:10.1007/s40279-023-01978-y · Cited by 61
Self-Determination Theory and Language Learning: A Multilevel Meta-Analysis
Alamer, A., Robat, E. S., Shirvan, M. E., & Ryan, R. M. (2025) · Educational Psychology Review · doi:10.1007/s10648-025-10038-y · Cited by 67
From Tools to Agents: Meta-Analytic Insights into Human Acceptance of AI
Li, B., Lai, E. Y., & Wang, X. (. (2025) · Journal of Marketing · doi:10.1177/00222429251355266 · Cited by 59
Goal orientation and performance adaptation: A meta-analysis
Stasielowicz, L. (2019) · Journal of Research in Personality · doi:10.1016/j.jrp.2019.103847 · Cited by 46
Boen, R., Quintana, D. S., Ladouceur, C. D., & Tamnes, C. K. (2022) · Psychophysiology · doi:10.1111/psyp.14003 · Cited by 40
“Thus, the final three- level meta- analytic model accounted for (i) variance of the effect sizes, (ii) between effect sizes from the same study, and (iii) between studies (Assink & Wibbelink, 2016).”
Methodvan der Storm, L., Lissa, C. J. V., Lucassen, N., Helmerhorst, K. O. W., & Keizer, R. (2021) · Marriage & Family Review · doi:10.1080/01494929.2021.1927931 · Cited by 50
Würtz, F., Zahler, L., Blackwell, S. E., Margraf, J., Bagheri, M., & Woud, M. L. (2022) · Clinical Psychology Review · doi:10.1016/j.cpr.2022.102133 · Cited by 52
Childhood adversity and vagal regulation: A systematic review and meta-analysis
Wesarg, C., van den Akker, A. L., Oei, N. Y. L., Wiers, R. W. H. J., Staaks, J. P. C., Thayer, J. F., Williams, D. P., & Hoeve, M. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104920 · Cited by 54
Yin, J., Yue, C., Song, Z., Sun, X., & Wen, X. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.05.037 · Cited by 48
Wearable Artificial Intelligence for Detecting Anxiety: Systematic Review and Meta-Analysis
Abd-Alrazaq, A. A., AlSaad, R., Harfouche, M., Aziz, S., Ahmed, A., Damseh, R., & Sheikh, J. I. (2023) · Journal of Medical Internet Research · doi:10.2196/48754 · Cited by 50
Yeo, T. E. D., Chu, T. H., & Li, Q. (2025) · Journal of Advertising Research · doi:10.1080/00218499.2025.2467763 · Cited by 44
Stasielowicz, L. (2020) · Personality and Individual Differences · doi:10.1016/j.paid.2020.110178 · Cited by 56
How universal is preference for visual curvature? A systematic review and meta‐analysis
Chuquichambi, E. G., Vartanian, O. A., Skov, M., Corradi, G. B., Nadal, M., Silvia, P. J., & Munar, E. (2022) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14919 · Cited by 51
Do Bandwagon Cues Affect Credibility Perceptions? A Meta-Analysis of the Experimental Evidence
Wang, S., Chu, T. H., & Huang, G. (2023) · Communication Research · doi:10.1177/00936502221124395 · Cited by 54
Yang, Y., & Konrath, S. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01681-y · Cited by 43
Bouwhuis, A., Koelen, J. A., Eurelings‐Bontekoe, L., Hoekstra-Oomen, C., & Glas, G. G. (2023) · Psychotherapy Research · doi:10.1080/10503307.2023.2241626 · Cited by 43
McNally, X., Webb, T. L., Smith, C., Moss, A., & Miller, J. G. (2024) · Conservation Biology · doi:10.1111/cobi.14237 · Cited by 46
Spry, E., Aarsman, S. R., Youssef, G. J., Patton, G. C., Macdonald, J. A., Sanson, A. V., Thomson, K., Hutchinson, D. M., Letcher, P., & Olsson, C. A. (2020) · Developmental Review · doi:10.1016/j.dr.2020.100934 · Cited by 52
Steubl, L., Sachser, C., Baumeister, H., & Domhardt, M. (2021) · European Journal of Psychotraumatology · doi:10.1080/20008198.2021.1879551 · Cited by 44
CBCT in dental age estimation: A systematic review and meta analysis
Boedi, R. M., Shepherd, S. D., Mânica, S., & Franco, A. (2022) · Dentomaxillofacial Radiology · doi:10.1259/dmfr.20210335 · Cited by 42
A Meta-Analysis of the Relationship Between Worry and Rumination
Stade, E. C., & Ruscio, A. M. (2022) · Clinical Psychological Science · doi:10.1177/21677026221131309 · Cited by 49
Linking Cognitive Reappraisal and Expressive Suppression to Mindfulness: A Three-Level Meta-Analysis
Zhou, S., Wu, Y., & Xu, X. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20021241 · Cited by 42
Wilson, C., Janes, G., Lawton, R., & Benn, J. J. (2023) · BMJ Quality & Safety · doi:10.1136/bmjqs-2022-015634 · Cited by 42
Chen, Y., Su, Q., Yang, J., Li, G., Zhang, S., Lv, Y., & Yu, L. (2023) · Frontiers in Physiology · doi:10.3389/fphys.2023.1202789 · Cited by 42
Stegen, H., Duppen, D., Savieri, P., Stas, L., Pan, H., Aartsen, M., Callewaert, H., Dierckx, E., & De Donder, L. (2024) · International Psychogeriatrics · doi:10.1017/s1041610224000425 · Cited by 42
Bennett, M. G., Schofield, K. A., Lee, S., & Norton, S. B. (2017) · Environmental Evidence · doi:10.1186/s13750-017-0097-8 · Cited by 44
Bonapersona, V., Joëls, M., & Sarabdjitsingh, R. A. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.09.003 · Cited by 44
Revisiting the effectiveness of study abroad language programs: A multi-level meta-analysis
Tseng, W., Liu, Y., Hsu, Y.-T., & Chu, H.-C. J. (2021) · Language Teaching Research · doi:10.1177/1362168820988423 · Cited by 53
Speech‐in‐noise perception in musicians and non‐musicians: A multi‐level meta-analysis
Hennessy, S., Mack, W. J., & Habibi, A. (2022) · Hearing Research · doi:10.1016/j.heares.2022.108442 · Cited by 50
Do motoneuron discharge rates slow with aging? A systematic review and meta-analysis
Orssatto, L. B. R., Borg, D. N., Pendrith, L., Blazevich, A. J., SHIELD, A. J., & Trajano, G. S. (2022) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2022.111647 · Cited by 41
Helland, S. S., Mellblom, A. V., Kjøbli, J., Wentzel‐Larsen, T., Espenes, K., Engell, T., & Kirkøen, B. (2022) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-022-01213-2 · Cited by 50
Protective Factors for Antisocial Behavior in Youth: What is the Meta-Analytic Evidence?
Gubbels, J., Assink, M., & van der Put, C. E. (2023) · Journal of Youth and Adolescence · doi:10.1007/s10964-023-01878-4 · Cited by 77
Self-citationWillems, Y. E., Li, J., Hendriks, A. M., Bartels, M., & Finkenauer, C. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15112468 · Cited by 48
Burgers, C. F., & Brugman, B. C. (2021) · Communication Research · doi:10.1177/00936502211032100 · Cited by 41
Xu, X., Liu, Z., Gong, S., & Wu, Y. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19031391 · Cited by 39
“Because there was more than one effect size in some included studies, we conducted multilevel meta-analysis of skills to analyze the data, which can cope with the dependency of effect sizes [62].”
BackgroundLei, H., Wang, X., Chiu, M. M., Du, M., & Xie, T. (2022) · School Psychology International · doi:10.1177/01430343221122453 · Cited by 56
Dong, M., Weststrate, N. M., & Fournier, M. A. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916221114096 · Cited by 51
Kong, F., Meng, S., Deng, H., Wang, M., & Sun, X. (2023) · Educational Psychology Review · doi:10.1007/s10648-023-09746-0 · Cited by 51
Doffer, D. P. A., Dekkers, T. J., Hornstra, R., der Oord, S. V., Luman, M., Leijten, P. H. O., Hoekstra, P. J., van den Hoofdakker, B. J., & Groenman, A. P. (2023) · JCPP Advances · doi:10.1002/jcv2.12196 · Cited by 39
Catalán, I. A., Auch, D., Kamermans, P., Morales-Nín, B., Angelopoulos, N. V., Reglero, P., Sandersfeld, T., & Peck, M. A. (2019) · Fish and Fisheries · doi:10.1111/faf.12359 · Cited by 43
Yeh, N., & Rose, N. S. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00993 · Cited by 41
Does dampness and mold in schools affect health? Results of a meta‐analysis
Fisk, W. J., Chan, W. R., & Johnson, A. L. (2019) · Indoor Air · doi:10.1111/ina.12588 · Cited by 45
The Social Information Processing Model in Child Physical Abuse and Neglect: A Meta-analytic Review
Camilo, C., Garrido, M. V., & Calheiros, M. M. (2020) · Child Abuse & Neglect · doi:10.1016/j.chiabu.2020.104666 · Cited by 37
Raccanello, D., Rocca, E., Barnaba, V., Vicentini, G., Hall, R., & Brondino, M. (2022) · Child & Youth Care Forum · doi:10.1007/s10566-022-09677-x · Cited by 52
Yao, X., Xu, X., Chan, K. L., Chen, S., Assink, M., & Gao, S. (2022) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.09.116 · Cited by 50
Self-citationA meta-analysis of the relationship between climate change experience and climate change perception
Xia, Z., Ye, J., Zhou, Y., Howe, P. D., Xu, M., Tan, X., Tian, X., & Zhang, C. (2022) · Environmental Research Communications · doi:10.1088/2515-7620/ac9bd9 · Cited by 39
Schäfer, S. K., Sopp, M. R., Fuchs, A., Kotzur, M., Maahs, L., & Michael, T. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2022.12.106 · Cited by 49
Kim, B., & Royle, M. L. (2024) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.14022 · Cited by 41
de Poll, M. J. W.-V., Roest, J. J., van der Stouwe, T., van den Akker, A. L., Stams, G. J. J. M., Escudero, V., Overbeek, G. J., & de Swart, J. (2017) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-017-0249-y · Cited by 44
Bernardino, J., Martins, R. C., Bispo, R., & Moreira, F. (2019) · Journal of Environmental Management · doi:10.1016/j.jenvman.2019.109651 · Cited by 38
How can adolescent aggression be reduced? A multi-level meta-analysis
Castillo-Eito, L., Armitage, C. J., Norman, P. E., Day, M. R., Doğru, O. C., & Rowe, R. (2020) · Clinical Psychology Review · doi:10.1016/j.cpr.2020.101853 · Cited by 57
Slodowicz, D., Durbecq, A., Ladouceur, E. R., Eschen, R., Humbert, J., & Arlettaz, R. (2023) · Ecological Solutions and Evidence · doi:10.1002/2688-8319.12221 · Cited by 38
Gutiérrez, B. C., & Leaper, C. (2023) · Sexuality & Culture · doi:10.1007/s12119-023-10127-6 · Cited by 50
Niu, X., Li, J.-Y., King, D. L., Rost, D. H., Wang, H., & Wang, J. (2023) · Journal of Behavioral Addictions · doi:10.1556/2006.2023.00043 · Cited by 45
The effects of school‐based interventions on physiological stress in adolescents: A meta‐analysis
van Loon, A. W. G., Creemers, H. E., Okorn, A., Vogelaar, S., Miers, A. C., Saab, N., Westenberg, P. M., & Asscher, J. J. (2021) · Stress and Health · doi:10.1002/smi.3081 · Cited by 44
Engell, T., Stadnick, N. A., Aarons, G. A., & Barnett, M. L. (2023) · Global Implementation Research and Applications · doi:10.1007/s43477-023-00077-4 · Cited by 37
Chi, K., Lee, P., Chowdhury, I. Z., Akman, Z., Mangalesh, S., Song, J., Satish, V., Babapour, G., Kang, Y., Schwartz, R., et al. (2024) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwae298 · Cited by 38
Yin, M., Xu, K., Deng, J., Deng, S., Chen, Z., Zhang, B., Zhong, Y., Li, H., Zhang, X., Toledo, M. J. L., et al. (2024) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.14769 · Cited by 43
Yin, M., Deng, S., Deng, J., Xu, K., Nassis, G. P., Girard, O., & Li, Y. (2025) · Journal of sport and health science/Journal of Sport and Health Science · doi:10.1016/j.jshs.2025.101030 · Cited by 43
Individual and Organizational Predictors of White-Collar Crime: A Meta-Analysis
Pusch, N., & Holtfreter, K. (2020) · Journal of White Collar and Corporate Crime · doi:10.1177/2631309x19901317 · Cited by 42
Family and couple integrated cognitive-behavioural therapy for adults with OCD: A meta-analysis
Stewart, K. E., Sumantry, D. M., & Malivoire, B. L. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.07.140 · Cited by 37
Mertens, E. C. A., Deković, M., Leijten, P. H. O., van Londen, M., & Reitz, E. (2020) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-020-00328-y · Cited by 51
Rominger, C., Schneider, M., Fink, A., Tran, U. S., Perchtold‐Stefan, C. M., & Schwerdtfeger, A. R. (2022) · Sports Medicine - Open · doi:10.1186/s40798-022-00444-9 · Cited by 47
Shushan, T., Lovell, R. J., Buchheit, M., Scott, T. J., Barrett, S., Norris, D., & McLaren, S. J. (2023) · Sports Medicine - Open · doi:10.1186/s40798-023-00564-w · Cited by 37
Cross-age peer mentoring for youth: A meta-analysis
Burton, S., Raposa, E. B., Poon, C. Y. S., Stams, G. J. J. M., & Rhodes, J. (2022) · American Journal of Community Psychology · doi:10.1002/ajcp.12579 · Cited by 38
Douziech, M., Conesa, I. R., Benítez‐López, A., Franco, A., Huijbregts, M. A. J., & Rosalie Van Zelm, F. (2018) · Environmental Science Processes & Impacts · doi:10.1039/c7em00493a · Cited by 36
Mauger, C., Lancelot, C., Roy, A., Coutant, R., Cantisano, N., & Gall, D. L. (2018) · Neuropsychology Review · doi:10.1007/s11065-018-9372-x · Cited by 36
Do educational games affect students' achievement emotions? Evidence from a meta‐analysis
Lei, H., Wang, C., Chiu, M. M., & Chen, S. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12664 · Cited by 40
Tourjman, V., Gill, L.-N., Ahmed, G., DuBow, A., Côté, H., Daly, N., Daoud, G., Espinet, S. D., Flood, J., Gagnier-Marandola, E., et al. (2022) · Brain Sciences · doi:10.3390/brainsci12081023 · Cited by 45
Child Maltreatment as a Risk Factor for Rejection Sensitivity: A Three-Level Meta-Analytic Review
Gao, S., Assink, M., Bi, C., & Chan, K. L. (2024) · Trauma, Violence, & Abuse · doi:10.1177/15248380231162979 · Cited by 41
Self-citationInterventions to Prevent Intimate Partner Violence: A Systematic Review and Meta-Analysis
Alsina, E., Browne, J. L., Gielkens, D., Noorman, M. A. J., & de Wit, J. B. F. (2023) · Violence Against Women · doi:10.1177/10778012231183660 · Cited by 40
Cui, X., Zhang, S., Yu, S., Ding, Q., & Li, X. (2024) · Behaviour Research and Therapy · doi:10.1016/j.brat.2024.104549 · Cited by 37
Bennett, M. G., Lee, S., Schofield, K. A., Ridley, C. E., Washington, B. J., & Gibbs, D. A. (2021) · Environmental Evidence · doi:10.1186/s13750-021-00238-8 · Cited by 37
The Influence of Diagnostic Labels on the Evaluation of Students: a Multilevel Meta-Analysis
Franz, D. J., Richter, T., Lenhard, W., Marx, P., Stein, R., & Ratz, C. (2023) · Educational Psychology Review · doi:10.1007/s10648-023-09716-6 · Cited by 43
Fang, S., & Ding, D. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1069748 · Cited by 34
The Two Sides of Cognitive Masking: A Three-Level Bayesian Meta-Analysis on Twice-Exceptionality
Atmaca, F., & Балоглу, М. (2022) · Gifted Child Quarterly · doi:10.1177/00169862221110875 · Cited by 44
The Association Between Child Abuse and Aggressive Behavior: A Three-Level Meta-Analysis
Ran, G., Zhang, Q., Zhang, Q., Li, J., & Chen, J. (2022) · Trauma Violence & Abuse · doi:10.1177/15248380221129596 · Cited by 34
The association between working memory and mathematical problem solving: A three-level meta-analysis
Ji, Z., & Guo, K. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1091126 · Cited by 58
Metadata
- Authors
- Assink, M., & Wibbelink, C. J. M.
- Affiliations
- University of Amsterdam (NL)
- Corresponding author
- Assink, Mark
- Venue
- The Quantitative Methods for Psychology
- Published
- 2016-10-01
- Volume
- 12
- Issue
- 3
- Pages
- 154-174
- ISSN
- 2292-1354 (ISSN-L)
- OpenAlex
- W2532414435
- Semantic Scholar
- 95f645af7a355ecf2b9a7958c12734ad1768e44f
- Cited by
- 1,330
- References
- 47
- Citations by year
- 2026: 345 · 2025: 244 · 2024: 208 · 2023: 146 · 2022: 134 · 2021: 93 · 2020: 81 · 2019: 44 · 2018: 22 · 2017: 9 · 2016: 2
- FWCI
- 21.40
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Quantitative Methods for Psychology (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Universiteit Maastricht
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- multilevel meta-analysis, R programming language, effect size heterogeneity, between-study variance, moderator analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
