2021 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 Manuscript. Supplementary tutorial. Supplementary data. 2020 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). 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 2019
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 2018 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 2017
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
2016 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
2015 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
2014 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. 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
2013 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 |