Marjolein Fokkema
Universitair hoofddocent
- Naam
- Dr. M. Fokkema
- Telefoon
- +31 71 527 7996
- m.fokkema@fsw.leidenuniv.nl
- ORCID iD
- 0000-0002-9252-8325
Marjolein Fokkema werkt aan statistische modellen (of, zoals we dat tegenwoordig vaak noemen: machine learning of artificial intelligence) en psychometrie en -diagnostiek. Marjolein is associate editor bij The European Journal of Psychological Assessment en lid van de Commissie Testaangelegenheden Nederland (COTAN) van het Nederlands Instituut van Psychologen (NIP).
Meer informatie over Marjolein Fokkema
Over Artificial Intelligence
Leiden Psychology Blog
Kort CV
Marjolein Fokkema werkt aan statistische modellen (of, zoals we dat tegenwoordig vaak noemen: machine learning of artificial intelligence) en psychometrie en -diagnostiek. Marjolein is associate editor bij The European Journal of Psychological Assessment en lid van de Commissie Testaangelegenheden Nederland (COTAN) van het Nederlands Instituut van Psychologen (NIP).
Onderzoek
Marjolein ontwikkelt methoden die transparante en begrijpelijke resultaten opleveren, die eenvoudig kunnen toegepast bij het maken van beslissingen in de (klinische) praktijk. Ze werkt het liefst aan beslisboommethoden: Statistische methoden die resultaten geven in de vorm van een beslisboom. Deze methoden zijn vaak net zo accuraat als meer complexe modellen, maar eenvoudiger te begrijpen en kunnen met minder informatie een beslissing of voorspelling maken.
Onderwijs
Marjolein doceert het mastervak Statistical Learning and Prediction aan het Instituut Psychologie en aan het Mathematisch Instituut. Ze doceert het bachelorvak Psychometrie aan het Psychologisch Instituut. Voorheen doceerde ze het mastervak Latent Variable Models.
Beurzen
- 2021: German Academic Exchange Service (DAAD) - 3-month stay at Max Planck Institute, Berlin (main applicant)
- 2017: Swiss National Science Foundation (SNF) - International Visit Grant for 6-month stay at University of Zurich (main applicant)
- 2017: ZonMW - Onderzoeksprogramma GGZ Middellange termijn (co-applicant)
- 2014: Psychometric Society - Student Travel Award (main applicant)
Relevante links
Universitair hoofddocent
- Faculteit der Sociale Wetenschappen
- Instituut Psychologie
- Methodologie & Statistiek
- 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): 1006.
- Rohrbach P.J., Dingemans A. E., Spinhoven P., Van Ginkel J.R., Fokkema M., Wildermans T.F., Bauer S. & Van Furth E.F. (2022), 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 55(10): 1361-1373.
- Iliescu D., Greiff S., Ziegler M. & Fokkema M. (2022), Artificial intelligence, machine learning, and other demons, European Journal of Psychological Assessment 38(3): 163-164.
- 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): 73-77.
- Fokkema M., Iliescu D., Greiff S., Ziegler M. & (2022), Machine Learning and Prediction in Psychological Assessment: Some Promises and Pitfalls, European Journal of Psychological Assessment 38(3): 165-175.
- Loon W.S. van, Vos F. de, Fokkema M., Szabo B.T., Koini M., Schmidt R. & Rooij M.J. de (2022), Analyzing hierarchical multi-view MRI Data With StaPLR An Application to Alzheimer's disease classification: an application to Alzheimer's disease classification, Frontiers in Neuroscience 16: 1-36 (830630).
- De Rooij M.J., Karch J.D., Fokkema M., Bakk Z., Pratiwi B.C. & Kelderman H. (2022), SEM-based out-of-sample predictions, Structural Equation Modeling: A Multidisciplinary Journal : 1-17.
- Driessen E., Fokkema M., Dekker J.J. M., Peen J., Van Henricus L. Maina Gi., Rosso G., Rigardetto S., Cuniberti F., Vitriol V.G., Andreoli A., Burnand Y., López R. J., Villamil S. V., Twisk J. W. R. & Wienicke F.J. Cuijpers P. (2022), 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.
- Wijn A.N. de, Fokkema M. & Doef M.P. van der (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.
- 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.
- 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): 329-341.
- Fokkema M. & Christoffersen B. (2021), pre: Prediction Rule Ensembles [software package and manual].
- Wijn A.N. de, Fokkema M. & Doef M. P. van der (2021), 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 : 1-11.
- 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 U. & Zeinoun P. (2021), Supporting academic freedom and living societal responsibility, European Journal of Psychological Assessment 37(2): .
- Loon W. van, Vos F. de, Fokkema M., Szabo B., Koini M., Schmidt R. & Rooij M. de (2021), Analyzing hierarchical multi-view MRI data with StaPLR: an application to Alzheimer's disease classification . [working paper].
- Markovitch B. & Fokkema M. (2021), Improved prediction rule ensembling through model-based data generation arXiv. [Working paper].
- Fokkema M Edbrooke-Childs J Wolpert M (2020), Generalized linear mixed-model (GLMM) trees: A flexible decision-tree method for multilevel and longitudinal data, Psychotherapy Research : 1-13.
- Fokkema M. (2020), Fitting prediction rule ensembles with R package pre, Journal of Statistical Software 92(12): 1-30.
- 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 and Adolescent Psychiatry 29: 167-178.
- Loon W.S. van, Fokkema M. & Szabo B.T. Rooij M.J. de (2020), Stacked penalized logistic regression for selecting views in multi-view learning, Information Fusion 61: 113-123.
- Fokkema M. & Strobl C. (2020), Fitting prediction rule ensembles to psychological research data: an introduction and tutorial, Psychological Methods 25(5): 636-652.
- Fokkema M Strobl C (2020), Fitting Prediction Rule Ensembles to Psychological Research Data: An Introduction and Tutorial, Psychological Methods : .
- Rohrbach P.J., Dingemans A.E., Spinhoven P., Van den Akker-Van Marle E., Van Ginkel J.R., Fokkema M., Moessner M., Bauer S. & Van Furth E.F. (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: e509.
- Fokkema M. & Zeileis A. (2019), glmertree: Generalized Linear Mixed Model Trees [software package and manual]: Fitting Generalized Linear Mixed-Effects Model Trees.
- 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.
- Driessen E., Abbass A.A., Barber J.P., Gibbons M.B.C., Dekker J.J.M., Fokkema M., Fonagy P., Hollon S.D., Jansma E.P., Maat S.C.M. de, Town J.M., Twisk J.W.R., Van Henricus L., Weitz E. & Cuijpers P. (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: e018900.
- 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.
- Ballegooijen W. van, Eikelenboom M., Fokkema M., Riper H., Hemert A.M. van, Kerkhof A.J.F.M., Penninx B.W.J.H. & Smit J.H. (2018), Comparing factor structures of depressed patients with and without suicidal ideation, A measurement invariance analysis, Journal of Affective Disorders 245: 180-187.
- 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.
- 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.
- Kraan T.C., Ising H.K., Fokkema M., Velthorst E., Berg D.P.G. van den, Kerkhoven M., Veling W., Smit F., Linszen D.H., Nieman D.H., Wunderink L., Boonstra N., Klaassen R.M.C., Dragt S., Rietdijk J., Haan L. de & Gaag M. van der (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.
- Meijer E., Van Laar C., Gebhardt W.A., Fokkema M., Van den Putte S.J.H.M., Dijkstra A., Fong G. & Willemsen M. (2017), Identity change among smokers and ex-smokers: Findings from the ITC Netherlands Survey, Psychology of Addictive Behaviors 31(4): 465-478.
- De Beurs D.P., Fokkema M. & O’Connor R.C. (2016), Optimizing the assessment of suicidal behavior: The application of curtailment techniques, Journal of Affective Disorders 196: 218-224.
- Fokkema M. (4 april 2016), London 2012: Curse or Blessing?!. Leiden Psychology Blog. Leiden: Leiden University. [blog].
- Fokkema M. (20 september 2016), Waiting time. Leiden Psychology Blog. Leiden: the Institute of Psychology and the Faculty of Social and Behavioural Sciences, Leiden University. [blog].
- Kraan T., Ising H., Fokkema M., Velthorst E., Berg van den D.P.G., Kerkhoven M., Veling W. Smit F., Linszen D.H., Nieman D.H., Wunderink L., Boonstra N., Klaassen R.M.C., Dragt S., Rietdijk J., Haan L. de & Gaag M. van der (2016), 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.
- Fokkema M., Smits N., Kelderman H. & Penninx B.W.J.H. (2015), Connecting clinical and actuarial prediction with rule-based methods, Psychological Assessment 27(2): 636-644.
- Fokkema M. (10 november 2015), Connecting clinical decision- making and psychological research with rule-based methods. Leiden Psychology Blog. Leiden: Leiden University. [blog].
- 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.
- Fokkema M., Smits N., Zeileis A., Hothorn T. & Kelderman H. (2015), Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees. Working paper. Working Papers in Economics and Statistics University of Innsbruck.
- 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.