Fokkema, M., & Zeileis, A. (2024). Subgroup detection in linear growth curve models with generalized linear mixed model (GLMM) trees. Behavior Research Methods. https://doi.org/10.3758/s13428-024-02389-1 

van Loon, W., Fokkema, M., Szabo, B., & de Rooij, M. (2024). View selection in multi-view stacking: choosing the meta-learner. Advances in Data Analysis and Classification.  https://doi.org/10.1007/s11634-024-00587-5 


Wang, M., Rücklin, M., Poelmann, R. E., de Mooij, C. L., Fokkema, M., Lamers, G. E., ... & Richardson, M. K. (2023). Nanoplastics causes extensive congenital malformations during embryonic development by passively targeting neural crest cells. Environment International, 173, 107865. https://doi.org/10.1016/j.envint.2023.107865 

De Rooij, M. Karch, J.D., Fokkema, M., Bakk, Z., Pratiwi, B.C., Kelderman, H. (2023). SEM-based out-of-sample predictions. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705511.2022.2061494  

Poot, C. C., Meijer, E., Fokkema, M., Chavannes, N. H., Osborne, R. H., & Kayser, L. (2023). Translation, cultural adaptation and validity assessment of the Dutch version of the eHealth Literacy Questionnaire: a mixed-method approach. BMC Public Health, 23(1), 1-17. https://doi.org/10.1186/s12889-023-15869-4 

Driessen, E., Fokkema, M., Dekker, J. J., Peen, J., Van, H. L., Maina, G., ... & Cuijpers, P. (2023). Which patients benefit from adding short-term psychodynamic psychotherapy to antidepressants in the treatment of depression? A systematic review and meta-analysis of individual participant data. Psychological Medicine, 1-12. https://doi.org/10.1017/S0033291722003270

Guineau, M. G., Ikani, N., Tiemens, B., Voshaar, R. O., Fokkema, M., & Hendriks, G. J. (2023). Age related differences in symptom networks of overall psychological functioning in a sample of patients diagnosed with anxiety, obsessive compulsive disorder, or posttraumatic stress disorder. Journal of Anxiety Disorders, 100, 102793. https://doi.org/10.1016/j.janxdis.2023.102793 

Driessen, E., Efthimiou, O., Wienicke, F. J., Breunese, J., Cuijpers, P., Debray, T. P., Fisher, D., Fokkema, M., Furukawa, T.A., Hollon, S., Mehta, A.H.P., Riley, R., Schmidt, M.R., Twisk, J.R., & Cohen, Z. D. Developing a multivariable prediction model to support personalized selection among five major empirically-supported treatments for adult depression. Study protocol of a systematic review and individual participant data network meta-analysis. https://osf.io/preprints/psyarxiv/nua87 


Fokkema, M., Iliescu, D., Greiff, S., & Ziegler, M. (2022). Machine learning and prediction in psychological assessment: Some promises and pittfalls. European Journal of Psychological Assessment 38(3), 165-175. https://doi.org/10.1027/1015-5759/a000714 

van Loon, W., de Vos, F., Fokkema, M., Szabo, B., Koini, M., Schmidt, R., & de Rooij, M. (2022). Analyzing hierarchical multi-view MRI data with StaPLR: An application to Alzheimer's disease classification. Frontiers in Neuroscience 16, 830630. https://doi.org/10.3389/fnins.2022.830630

van Loon, W., Fokkema, M., & de Rooij, M. (2022). Imputation of missing values in multi-view data. arXiv preprint arXiv:2210.14484. https://arxiv.org/abs/2210.14484 

de Wijn, A.N., Fokkema, M., Van der Doef, M. (2022). The prevalence of stress-related outcomes and occupational well-being among emergency nurses in the Netherlands and the role of job factors: A regression tree analysis. Journal of Nursing Management 30(1), 187-197. https://doi.org/10.1111/jonm.13457

Rohrbach, P. J., Dingemans, A. E., Spinhoven, P., Van Ginkel, J. R., Fokkema, M., Wilderjans, T. F., ... & Van Furth, E. F. (in press). Effectiveness of an online self‐help program, expert‐patient support, and their combination for eating disorders: Results from a randomized controlled trial. International Journal of Eating Disorders. https://doi.org/10.1002/eat.23785 

Iliescu, D., Greiff, S., Ziegler, M., & Fokkema, M. (in press). Artificial intelligence, machine learning, and other demons. European Journal of Psychological Assessment 38(3), 163-164. https://doi.org/10.1027/1015-5759/a000713 

Iliescu, D., Rusu, A., Greiff, S., Fokkema, M. & Scherer, R. (2022). Why we need systematic reviews and meta-analyses in the testing and assessment literature. European Journal of Psychological Assessment, 38(2). https://doi.org/10.1027/1015-5759/a000705  


Markovitch, B., & Fokkema, M. (2021). Improved prediction rule ensembling through model-based data generation. arXiv preprint arXiv:2109.13672https://arxiv.org/abs/2109.13672

Chekroud, A. M., Bondar, J., Delgadillo, J., Doherty, G., Wasil, A., Fokkema, M., Cohen, Z., Belgrave, D., DeRubeis, R., Iniesta, R., Dwyer, D., Choi, K. (2021). The promise of machine learning in predicting treatment outcomes in psychiatry. World Psychiatry, 20(2), 154-170. https://doi.org/10.1002/wps.20882

Fokkema, M., Edbrooke-Childs, J. & Wolpert, M. (2021). Generalized linear mixed-model (GLMM) trees: A flexible decision-tree method for multilevel and longitudinal data. Psychotherapy Research, 31(3), 313-325. https://doi.org/10.1080/10503307.2020.1785037 

Iliescu, D., Greiff, S., Proyer, R., Ziegler, M., Allen, M., Claes, L., Fokkema, M., Hasking, P., Hiemstra, A., Maes, M., Mund, M., Nye, C., Scherer, R., Wetzel, E. & Zeinoun, P. (2021). Supporting Academic Freedom and Living Societal Responsibility. European Journal of Psychological Assessment, 37(2), 81-85.


Fokkema, M. (2020). Fitting prediction rule ensembles with R package pre. Journal of Statistical Software, 92(12), 1-30. http://doi.org/10.18637/jss.v092.i12

Fokkema, M. & Strobl, C. (2020). Fitting prediction rule ensembles to psychological research data: An introduction and tutorial. Psychological Methods 25(5), 636–652. http://doi.org/10.1037/met0000256   https://arxiv.org/abs/1907.05302

van Loon, W., Fokkema, M., Szabo, B., de Rooij, M. (2020). Stacked penalized logistic regression for selecting views in multi-view learning. Information Fusion, 61, 113-123. https://doi.org/10.1016/j.inffus.2020.03.007

Van Loon, W., Fokkema, M., Szabo, B., De Rooij, M. (2020). Multi-view stacking: Choosing the meta-learner. https://arxiv.org/abs/2010.16271

Wolpert, M., Zamperoni, V., Napoleone, E., Patalay, P., Jacob, J., Fokkema, M., Promberger, M., Costa da Silva, L., Patel, M., & Edbrooke-Childs, J. (2020). Predicting mental health improvement and deterioration in a large community sample of 11- to 13-year-olds. European Child & Adolescent Psychiatry. http://doi.org/10.1007/s00787-019-01334-4


van Ballegooijen, W., Eikelenboom, M., Fokkema, M., Riper, H., van Hemert, A. M., Kerkhof, A. J., ... & Smit, J. H. (2019). Comparing factor structures of depressed patients with and without suicidal ideation, a measurement invariance analysis. Journal of Affective Disorders, 245, 180-187. http://doi.org/10.1016/j.jad.2018.10.108

Rohrbach, P., Dingemans, A.E., Spinhove, P., Van Ginkel, J., Fokkema, M., Van den Akker-Van Marle, E., Van Furth, E., Moessner, M. & Bauer, S. (2019). A randomized controlled trial of an internet-based intervention for eating disorders and the added value of expert-patient support: study protocol. Trials 20, 509. http://doi.org/10.1186/s13063-019-3574-2

de Rooij, M., Pratiwi, B.C., Fokkema, M., Dusseldorp, E. & Kelderman, H. (2019). The Early Roots of Statistical Learning in the Psychometric Literature: A review and two new results. Preprint: arxiv:1911.11463


Fokkema, M., Smits, N., Zeileis, A., Hothorn, T. & Kelderman, H. (2018). Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees. Behavior Research Methods, 50(5), 2016-2034.  http://doi.org/10.3758/s13428-017-0971-x

Fokkema, M. & Greiff, S. (2018). Would you prefer your coefficients with a little bias, or rather with a lot of variance? European Journal of Psychological Assessment, 34(6), 363-366. http://doi.org/10.1027/1015-5759/a000514

Driessen, E., Abbass, A. A., Barber, J. P., Gibbons, M. B. C., Dekker, J. J., Fokkema, M., ... & Town, J. M. (2018). Which patients benefit specifically from short-term psychodynamic psychotherapy (STPP) for depression? Study protocol of a systematic review and meta-analysis of individual participant data. BMJ open, 8(2), e018900. http://doi.org/10.1136/bmjopen-2017-018900


Fokkema, M., & Greiff, S. (2017). How performing PCA and CFA on the same data equals trouble. European Journal of Psychological Assessment, 33(6), 399–402. http://doi.org/10.1027/1015-5759/a000460

Aardoom, J.J., Dingemans, A.E., Fokkema, M., Spinhoven, P., & Van Furth, E.F. (2017). Moderators of change in an Internet-based intervention for eating disorders with different levels of therapist support: What works for whom? Behaviour Research and Therapy, 89, 66-74. http://doi.org/10.1016/j.brat.2016.11.012

Kraan, T. C., Ising, H. K., Fokkema, M., Velthorst, E., van den Berg, D. P., Kerkhoven, M., ... & Wunderink, L. (2017). The effect of childhood adversity on 4-year outcome in individuals at ultra high risk for psychosis in the Dutch Early Detection Intervention Evaluation (EDIE-NL) Trial. Psychiatry Research, 247, 55-62. http://doi.org/10.1016/j.psychres.2016.11.014

Meijer, E., Van Laar, C., Gebhardt, W.A., Fokkema, M., Van den Putte, B., Dijkstra, A., Fong, G. T., & Willemsen, M.C. (2017). Identity change among smokers and ex-smokers: Findings from the ITC Netherlands survey. Psychology of Addictive Behaviors, 31(4), 465-478.http://doi.org/10.1037/adb0000281


De Beurs, D. Fokkema, M., O'Connor, R. (2016). Optimizing the assessment of suicidal behavior: The application of curtailment techniques. Journal of Affective Disorders, 196, 218-224. http://doi.org/10.1016/j.jad.2016.02.033


De Beurs, D.P., Fokkema, M., De Groot, M.H., De Keijser, J. & Kerkhof, A.J.F.M. (2015). Longitudinal measurement invariance of the Beck Scale for Suicide Ideation. Psychiatry Research, 225(3), 368–373. http://doi.org/10.1016/j.psychres.2014.11.075

Fokkema, M., Smits, N., Kelderman, & Penninx, B.W.J.H. (2015). Connecting clinical and actuarial prediction with rule-based methods. Psychological Assessment, 27(2), 636-644. http://doi.org/10.1037/pas0000072

Zhang, B., Gao, Q., Fokkema, M., Alterman, V., Liu, & Q. (2015). Adolescent Interpersonal Relationships, Social Support and Loneliness in High Schools: Mediation Effect and Gender Differences. Social Science Research, 53, 104–117. http://doi.org/10.1016/j.ssresearch.2015.05.003


Fokkema, M., Smits, N., Finkelman, M. D., Kelderman, H., & Cuijpers, P. (2014). Curtailment: A method to reduce the length of self-report questionnaires while maintaining diagnostic accuracy. Psychiatry Research, 215(2), 477-482. http://doi.org/10.1016/j.psychres.2013.11.003

Fokkema, M., Smits, N., Kelderman, H., Carlier, I. V., & Van Hemert, A. M. (2014). Combining decision trees and stochastic curtailment for assessment length reduction of test batteries used for classification. Applied Psychological Measurement, 38(1), 3-17. http://doi.org/10.1177/0146621613494466

Geraedts, A.S., Fokkema, M., Kleiboer, A.M., Smit, F., Wiezer, N.W., Majo, M.C., Van Mechelen, W., Cuijpers, P., & Penninx, B.W.J.H. (2014). The longitudinal prediction of costs due to health care uptake and productivity losses in a cohort of employees with and without depression or anxiety. Journal of Occupational and Environmental Medicine, 56(8), 794-801. http://doi.org/10.1097/JOM.0000000000000234


Fokkema, M., Smits, N., Kelderman, H., & Cuijpers, P. (2013). Response shifts in mental health interventions: An illustration of longitudinal measurement invariance. Psychological Assessment, 25(2), 520-531. http://doi.org/10.1037/a0031669

Rietdijk, J., Fokkema, M., Stahl, D., Valmaggia, L., Ising, H. K., Dragt, S., ... , van der Gaag, M. (2013). The distribution of self-reported psychotic-like experiences in non-psychotic help-seeking mental health patients in the general population; a factor mixture analysis. Social Psychiatry and Psychiatric Epidemiology, 49(3), 349-358. http://doi.org/10.1007/s00127-013-0772-1

2011 and before

Zhang, B., Fokkema, M., Cuijpers, P., Li, J., Smits, N., & Beekman, A. (2011). Measurement invariance of the center for epidemiological studies depression scale (CES-D) among Chinese and Dutch elderly. BMC Medical Research Methodology, 11(1), 74. http://doi.org/10.1186/1471-2288-11-74

De Wit, L. M., Fokkema, M., van Straten, A., Lamers, F., Cuijpers, P., & Penninx, B. W. (2010). Depressive and anxiety disorders and the association with obesity, physical, and social activities. Depression and Anxiety, 27(11), 1057-1065. http://doi.org/10.1002/da.20738