Dr. J.M.B. (Jonas) Haslbeck
Faculty of Social and Behavioural Sciences
Programme group Psychological Methods
Area of expertise: Statistical Modeling, Computational Modeling, Natural Language Processing
Visiting address
- Nieuwe Achtergracht 129
Postal address
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Postbus 15906
1001 NK Amsterdam
Contact details
Social media
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Profile
I am working as a Veni-funded Postdoctoral Researcher at the Psychological Methods group at the University of Amsterdam, where I am part of the Bayesian Graphical Modeling Lab, the Theory Methods Lab, and the Psychosystems group. I am also partially funded by the New Science of Mental Disorders (NSMD) gravitation consortium, for which I provide trainings and statistical consultation.
Research expertise
- Statistical Modeling
- Computational Modeling
- Natural Language Processing
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Publications
2026
- Aarts, E., & Haslbeck, J. M. B. (in press). Modelling Psychological Time Series with Multilevel Hidden Markov Models: A Tutorial. Psychological Methods. https://osf.io/preprints/psyarxiv/prm3t_v1
Ernst, A. F., & Haslbeck, J. M. B. (2026). Modeling Qualitative Between-Person Heterogeneity in Time-Series using Latent Class Vector Autoregressive Models. Behavior Research Methods, 58(1), Article 28. https://doi.org/10.3758/s13428-025-02909-7 [details]- Huth, K. B. S., Haslbeck, J. M. B., Keetelaar, S., van Holst, R. J., & Marsman, M. (2026). Statistical Evidence in Psychological Networks. Nature Human Behaviour, 10(2), 333-346. https://doi.org/10.1038/s41562-025-02314-2 [details]
- Schumacher, L., Kriston, L., Ebrahimi, O. V., Finnemann, A. T. K., Klein, J. F., & Haslbeck, J. M. B. (2026). A data re-analysis confirms the value of symptom networks in predicting psychotherapy outcome. World psychiatry, 25(1), 152-154. https://doi.org/10.1002/wps.70021 [details]
2025
- Aarts, E., & Haslbeck, J. M. B. (2025). Modelling Psychological Time Series with Multilevel Hidden Markov Models: A Numerical Evaluation. Manuscript submitted for publication. https://doi.org/10.31234/osf.io/y2u5s
- Boot, J., de Ron, J., Haslbeck, J. M. B., & Epskamp, S. (2025). Correcting for selection bias after conditioning on a sum-score in the Ising model. Behavior Research Methods, 57(12), Article 341. https://doi.org/10.3758/s13428-025-02820-1 [details]
- Dablander, F., Cologna, V., Sachisthal, M. S. M., & Haslbeck, J. M. B. (2025). Techno-optimistic scientists take fewer climate actions. Manuscript submitted for publication. https://osf.io/preprints/psyarxiv/c3skb_v1
- Dablander, F., Wimmer, S., & Haslbeck, J. (2025). Media Coverage of Climate Activist Groups in Germany. Climatic Change, 178(8), Article 144. https://doi.org/10.31234/osf.io/yhn54, https://doi.org/10.1007/s10584-025-03959-8 [details]
- Dablander, F., Wimmer, S., & Haslbeck, J. M. B. (2025). Mapping Climate Change Coverage: Causes, Consequences, and Solutions in German News Media, 2010–2024. Manuscript submitted for publication. https://osf.io/preprints/socarxiv/mv2q6_v1
- Delamain, H., Haslbeck, J. M. B., Shaikh, M., Buckman, J. E. J., Jena, R., Saunders, R., Stott, J., Suh, J. W., Pilling, S., & O'Discoll, C. (2025). Investigating differences in common mental health symptom expression and co-occurrence across ethnicities. Manuscript submitted for publication.
- Guenole, N., D'Urso, D., Samo, A., Sun, T., & Haslbeck, J. M. B. (2025). Enhancing Scale Development: Pseudo Factor Analysis of Language Embedding Similarity Matrices. Manuscript submitted for publication. https://osf.io/preprints/psyarxiv/vf3se_v2
- Haslbeck, J. M. B., Epskamp, S., & Waldorp, L. J. (2025). Testing for group differences in multilevel vector autoregressive models. Behavior Research Methods, 57(3), Article 100. https://doi.org/10.31234/osf.io/dhp8s, https://doi.org/10.3758/s13428-024-02541-x [details]
- Haslbeck, J. M. B., Jongerling, J., Siepe, B., Epskamp, S., & Waldorp, L. J. (2025). Model Checking for Vector Autoregressive Models. Manuscript submitted for publication. https://osf.io/preprints/psyarxiv/k6uz4_v2
- Haslbeck, J. M. B., Jover Martínez, A., Roefs, A. J., Fried, E. I., Lemmens, L. H. J. M., Groot, E., & Edelsbrunner, P. (2025). Comparing Likert and Visual Analogue Scales in Ecological Momentary Assessment. Behavior Research Methods, 57, Article 217. https://doi.org/10.3758/s13428-025-02706-2 [details]
- Hülsheger, U. R., Haslbeck, J. M. B., Jongerling, J., Fleuren, B., Verduyn, A., Nübold, A., & Uitdewilligen, S. (2025). A Dynamic Network Perspective on the Challenge Hindrance Stressor Framework: Unraveling the Dynamic Interplay of Stressors, Affect, and Work Engagement.. Manuscript submitted for publication.
- Jover Martinzez, A., Lemmens, L. H. J. M., Fried, E. I., Haslbeck, J. M. B., & Roefs, A. (2025). Does the structure of dynamic symptom networks depend on baseline psychopathology in students? Behaviour Research and Therapy, 195, Article 104888. https://doi.org/10.1016/j.brat.2025.104888 [details]
- Marsman, M., Waldorp, L. J., Sekulovski, N., & Haslbeck, J. (2025). Bayes Factor Tests for Group Differences in Ordinal and Binary Graphical Models. Psychometrika, 90(5), 1809-1842. https://doi.org/10.1017/psy.2025.10060 [details]
- Marsman, M., van den Bergh, D., & Haslbeck, J. M. B. (2025). Bayesian Analysis of the Ordinal Markov Random Field. Psychometrika, 90(1), 146-182. https://doi.org/10.1017/psy.2024.4 [details]
- Moshe, I., Haslbeck, J., Terhorst, Y., Paganini, S., Schlicker, S., Baumeister, H., & Sander, L. (2025). Network Intervention Analysis of a Digital Intervention for the Prevention of Depression in Patients with Chronic Back Pain. Behaviour Research and Therapy, 192, Article 104784. https://doi.org/10.1016/j.brat.2025.104784 [details]
- Peterson, F., Haslbeck, J. M. B., Tendeiro, J. N., Langener, A. M., Kas, M. J. H., Rizopoulos, D., & Bringmann, L. (in press). Comparing Training Window Selection Methods for Prediction in Non-Stationarity Time Series. British Journal of Mathematical & Statistical Psychology.
- Petter, J., Mehta, A., Petrova, K., Kindt, M., Sheppes, G., Haslbeck, J. M. B., & Gross, J. J. (2025). Emotion Regulation, Fast or Slow: A Computational Model of Strategy Choice. Emotion, 25(5), 1273-1292. https://doi.org/10.1037/emo0001471 [details]
- Ryan, O., Dablander, F., & Haslbeck, J. M. B. (2025). Toward a Generative Model for Emotion Dynamics. Psychological Review, 132(2), 416–441. https://doi.org/10.31234/osf.io/5fqtr, https://doi.org/10.1037/rev0000513 [details]
- Ryan, O., Haslbeck, J. M. B., & Robinaugh, D. J. (2025). Improving treatments for mental disorders using computational models. Behaviour Research and Therapy, 189, Article 104706. https://doi.org/10.31234/osf.io/tyn9z, https://doi.org/10.1016/j.brat.2025.104706 [details]
- Ryan, O., Haslbeck, J. M. B., & Waldorp, L. J. (2025). Non-Stationarity in Time-Series Analysis: Modeling Stochastic and Deterministic Trends. Multivariate Behavioral Research, 60(3), 556-588. https://doi.org/10.1080/00273171.2024.2436413 [details]
- Sekulovski, N., Arena, G., Haslbeck, J. M. B., Huth, K. B. S., Friel, N., & Marsman, M. (2025). A Stochastic Block Prior for Clustering in Graphical Models. Manuscript submitted for publication. https://osf.io/preprints/psyarxiv/29p3m_v1
- Sekulovski, N., Blanken, T. F., Haslbeck, J. M. B., & Marsman, M. (2025). The impact of dichotomization on network recovery. Behavior Research Methods, 57(12), Article 342. https://doi.org/10.3758/s13428-025-02861-6 [details]
- Siepe, B., Haslbeck, J. M. B., Kloft, M., Büchner, A., Zhang, Y., Fried, E. I., & Heck, D. W. (2025). Introducing openESM: A database of openly available experience sampling datasets. Manuscript submitted for publication. https://osf.io/preprints/psyarxiv/qfdtb_v1/
- Wulff, D., Kieslich, P., Henninger, F., Haslbeck, J. M. B., & Schulte-Mecklenbeck, M. (2025). Movement tracking of cognitive processes: A tutorial using mousetrap. Behavior Research Methods, 57(11), Article 307. https://doi.org/10.3758/s13428-025-02695-2 [details]
- van Dongen, N., van Bork, R., Finnemann, A., Haslbeck, J. M. B., van der Maas, H. L. J., Robinaugh, D. J., de Ron, J., Sprenger, J., & Borsboom, D. (2025). Productive Explanation: A Framework for Evaluating Explanations in Psychological Science. Psychological Review, 132(2), 311-329. https://doi.org/10.1037/rev0000479 [details]
- van Dongen, N., van Bork, R., Finnemann, A., Haslbeck, J. M. B., van der Maas, H. L. J., Robinaugh, D. J., de Ron, J., Sprenger, J., & Borsboom, D. (2025). Productive Explanation: A Framework for Evaluating Explanations in Psychological Science. Psychological Review, 132(2), 311-329. https://doi.org/10.31234/osf.io/qd69g, https://doi.org/10.1037/rev0000479 [details]
- van der Pal, Z., Geurts, H. M., Haslbeck, J. M. B., van Keeken, A., Bruijn, A. M., Douw, L., van Rooij, D., Franke, B., Buitelaar, J., Lambregts-Rommelse, N., Hartman, C., Oosterlaan, J., Luman, M., Reneman, L., Hoekstra, P. J., Blanken, T. F., & Schrantee, A. (2025). Stimulant medication and symptom interrelations in children, adolescents and adults with attention-deficit/hyperactivity disorder. European Child and Adolescent Psychiatry, 34(6), 1917–1929. https://doi.org/10.1007/s00787-024-02610-8 [details]
- van der Wijk, G., Huygelier, H., Haslbeck, J., Evers, A. W. M., Peters, M. L., Teppers, M., & Vlaeyen, J. W. S. (2025). A Network Analysis of Fear-Avoidance Beliefs, Mood and Disability in Chronic Pain. The Clinical Journal of Pain, 41(12), Article e1322. https://doi.org/10.1097/AJP.0000000000001322 [details]
2024
- Barnby, J. M., Haslbeck, J. M. B., Rosen, C., Sharma, P., & Harrow, M. (2024). Modelling the Longitudinal Dynamics of Paranoia in Psychosis: A Temporal Network Analysis Over 20 Years. Schizophrenia Research, 270, 465-475. https://doi.org/10.1016/j.schres.2024.06.055 [details]
- Borsboom, D., & Haslbeck, J. (2024). Integrating Intra- and Interindividual Phenomena in Psychological Theories. Multivariate Behavioral Research, 59(6), 1290-1309. https://doi.org/10.1080/00273171.2024.2336178 [details]
- Briganti, G., Scutari, M., Epskamp, S., Borsboom, D., Hoekstra, R. H. A., Fernandes Golino, H., Christensen, A. P., Morvan, Y., Ebrahimi, O. V., Costantini, G., Heeren, A., de Ron, J., Bringmann, L. F., Huth, K., Haslbeck, J. M. B., Isvoranu, A.-M., Marsman, M., Blanken, T., Gilbert, A., ... McNally, R. J. (2024). Network analysis: An overview for mental health research. International Journal of Methods in Psychiatric Research, 33(4), Article e2034. https://doi.org/10.1002/mpr.2034 [details]
- Dablander, F., Sachisthal, M. S. M., & Haslbeck, J. M. B. (2024). Climate Actions by Climate and Non-Climate Researchers. npj Climate Action, 3, Article 105. https://doi.org/10.1038/s44168-024-00187-1 [details]
- Dablander, F., Sachisthal, M. S. M., Cologna, V., Strahm, N., Bosshard, A., Grüning, N.-M., Green, A. J. K., Brick, C., Aron, A. R., & Haslbeck, J. M. B. (2024). Climate change engagement of scientists. Nature Climate Change, 14, 1033-1039. https://doi.org/10.1038/s41558-024-02091-2 [details]
- Fritz, J., Stochl, J., Haslbeck, J. M. B., Widmer, B., Galanta, J., Moore, M., Carey, E. G., Allen, C., Acton, N., Jonas, P. B., & Ford, T. J. (2024). Lessons Learned from the COVID-19 Pandemic: An Intensive Longitudinal Study Exploring the Dynamic Ecosystem of Psychosocial Factors and Mental Distress Among College Students. Manuscript submitted for publication. https://osf.io/preprints/osf/scy4h
- Haslbeck, J. M. B., & van Bork, R. (2024). Estimating the Number of Factors in Exploratory Factor Analysis via out-of-sample Prediction Errors. Psychological Methods, 29(1), 48-64. https://doi.org/10.31234/osf.io/qktsd, https://doi.org/10.1037/met0000528 [details]
- Haslbeck, J., & Epskamp, S. (2024). Observed Correlations between Person-means Depend on Within-person Correlations. Advances.in/psychology, 2, Article e853425. https://doi.org/10.56296/aip00020 [details]
- Robinaugh, D. J., Haslbeck, J. M. B., Waldorp, L. J., Kossakowski, J. J., Fried, E. I., Millner, A. J., McNally, R. J., Ryan, O., de Ron, J., van der Maas, H. L. J., van Nes, E. H., Scheffer, M., Kendler, K. S., & Borsboom, D. (2024). Advancing the network theory of mental disorders: A computational model of panic disorder. Psychological Review, 131(6), 1482-1508. https://doi.org/10.31234/osf.io/km37w, https://doi.org/10.1037/rev0000515 [details]
- Sekulovski, N., Keetelaar, S., Haslbeck, J., & Marsman, M. (2024). Sensitivity analysis of prior distributions in Bayesian graphical modeling: Guiding informed prior choices for conditional independence testing. Advances.in/psychology, 2, Article e92355. https://doi.org/10.56296/aip00016 [details]
- Waldorp, L., & Haslbeck, J. (2024). Network Inference with the Lasso. Multivariate Behavioral Research, 59(4), 738-757. https://doi.org/10.1080/00273171.2024.2317928 [details]
- Wallner, T. S., Haslbeck, J. M. B., Magnier, L., & Mugge, R. (2024). A network analysis of factors influencing the purchase intentions for refurbished electronics. Sustainable Production and Consumption, 46, 617-628. https://doi.org/10.1016/j.spc.2024.03.009 [details]
2023
- Burger, J., Isvoranu, A.-M., Lunansky, G., Haslbeck, J. M. B., Epskamp, S., Hoekstra, R. H. A., Fried, E. I., Borsboom, D., & Blanken, T. F. (2023). Reporting Standards for Psychological Network Analyses in Cross-Sectional Data. Psychological Methods, 28(4), 806–824. https://doi.org/10.31234/osf.io/4y9nz, https://doi.org/10.1037/met0000471 [details]
- Fishbein, J. N., Haslbeck, J., & Arch, J. J. (2023). Network intervention analysis of anxiety-related outcomes and processes of acceptance and commitment therapy (ACT) for anxious cancer survivors. Behaviour Research and Therapy, 162, Article 104266. https://doi.org/10.31234/osf.io/yt84w, https://doi.org/10.1016/j.brat.2023.104266 [details]
- Gossage, L. E., Narayanan, A., Dipnall, J. F., Berk, M., Sumich, A., Haslbeck, J. M. B., Iusitinij, L., Wrapson, W., Tautolo, E.-S., & Siegert, R. (2023). Understanding suicidality in Pacific adolescents in New Zealand using network analysis. Suicide and Life-Threatening Behavior, 53(5), 826-842. https://doi.org/10.1111/sltb.12986 [details]
- Haslbeck, J. M. B., Vermunt, J. K., & Waldorp, L. J. (2023). The Impact of Ordinal Scales on Gaussian Mixture Recovery. Behavior Research Methods, 55(4), 2143-2156. https://doi.org/10.3758/s13428-022-01883-8 [details]
- Haslbeck, J., Ryan, O., & Dablander, F. (2023). Multimodality and Skewness in Emotion Time Series. Emotion, 23(8), 2117-2141. https://doi.org/10.1037/emo0001218 [details]
- Verwimp, C., Tijms, J., Snellings, P., Haslbeck, J. M. B., & Wiers, R. W. (2023). A network approach to dyslexia: Mapping the reading network. Development and Psychopathology, 35(3), 1011-1025. https://doi.org/10.1017/S0954579421000365 [details]
- van der Wal, J. M., van Borkulo, C. D., Haslbeck, J. M. B., Slofstra, C., Klein, N. S., Blanken, T. F., Deserno, M. K., Lok, A., Nauta, M. H., & Bockting, C. L. (2023). Differential impact of preventive cognitive therapy while tapering antidepressants versus maintenance antidepressant treatment on affect fluctuations and individual affect networks and impact on relapse: a secondary analysis of a randomised controlled trial. EClinicalMedicine, 66, Article 102329. https://doi.org/10.1016/j.eclinm.2023.102329 [details]
2022
- Dalege, J., Haslbeck, J. M. B., & Marsman, M. (2022). Idealized Modeling of Psychological Dynamics. In A.-M. Isvoranu, S. Epskamp, L. Waldrop, & D. Borsboom (Eds.), Network Psychometrics with R: A Guide for Behavioral and Social Scientists (pp. 233-245). (Research methods and statistics). Routledge. https://doi.org/10.4324/9781003111238-17 [details]
- Epskamp, S., Haslbeck, J. M. B., Isvoranu, A.-M., & van Borkulo, C. D. (2022). Pairwise Markov Random Fields. In A.-M. Isvoranu, S. Epskamp, L. J. Waldrop, & D. Borsboom (Eds.), Network Psychometrics with R: A Guide for Behavioral and Social Scientists (pp. 93-110). (Research methods and statistics). Routledge. https://doi.org/10.4324/9781003111238-8 [details]
- Haslbeck, J. M. B. (2022). Estimating Group Differences in Network Models using Moderation Analysis. Behavior Research Methods, 54(1), 522-540. https://doi.org/10.3758/s13428-021-01637-y [details]
- Haslbeck, J. M. B., & Ryan, O. (2022). Recovering Within-Person Dynamics from Psychological Time Series. Multivariate Behavioral Research, 57(5), 735-766. https://doi.org/10.31234/osf.io/kcv3s, https://doi.org/10.31234/osf.io/dymhw, https://doi.org/10.1080/00273171.2021.1896353 [details]
- Haslbeck, J. M. B., Ryan, O., & Dablander, F. (2022). The Sum of All Fears: Comparing Networks Based on Symptom Sum-Scores. Psychological Methods, 27(6), 1061-1068. https://doi.org/10.1037/met0000418 [details]
- Haslbeck, J. M. B., Ryan, O., Robinaugh, D. J., Waldorp, L. J., & Borsboom, D. (2022). Modeling Psychopathology: From Data Models to Formal Theories. Psychological Methods, 27(6), 930-957. https://doi.org/10.31234/osf.io/jgm7f, https://doi.org/10.1037/met0000303 [details]
- Haslbeck, J. M. B., Ryan, O., van der Maas, H. L. J., & Waldorp, L. J. (2022). Modeling Change in Networks. In A.-M. Isvoranu, S. Epskamp, L. Waldrop, & D. Borsboom (Eds.), Network Psychometrics with R: A Guide for Behavioral and Social Scientists (pp. 193-209). (Research methods and statistics). Routledge. https://doi.org/10.4324/9781003111238-14 [details]
2021
- Aalbers, G., Engels, T., Haslbeck, J. M. B., Borsboom, D., & Arntz, A. (2021). The network structure of schema modes. Clinical Psychology and Psychotherapy, 28(5), 1065-1078. https://doi.org/10.1002/cpp.2577 [details]
- Haslbeck, J. M. B., Borsboom, D., & Waldorp, L. J. (2021). Moderated Network Models. Multivariate Behavioral Research, 56(2), 256-287. Advance online publication. https://doi.org/10.1080/00273171.2019.1677207 [details]
- Haslbeck, J. M. B., Bringmann, L. F., & Waldorp, L. J. (2021). A Tutorial on Estimating Time-Varying Vector Autoregressive Models. Multivariate Behavioral Research, 56(1), 120-149. https://doi.org/10.1080/00273171.2020.1743630 [details]
- Haslbeck, J. M. B., Epskamp, S., Marsman, M., & Waldorp, L. J. (2021). Interpreting the Ising Model: The Input Matters. Multivariate Behavioral Research, 56(2), 303-313. https://doi.org/10.1080/00273171.2020.1730150 [details]
- Hinze, V., Ford, T., Crane, C., Haslbeck, J. M. B., Hawton, K., Gjelsvik, B., & The MYRIAD Team (2021). Does depression moderate the relationship between pain and suicidality in adolescence? A moderated network analysis. Journal of Affective Disorders, 292, 667-677. https://doi.org/10.1016/j.jad.2021.05.100 [details]
- Lunansky, G., van Borkulo, C. D., Haslbeck, J. M. B., van der Linden, M. A., Garay, C. J., Etchevers, M. J., & Borsboom, D. (2021). The Mental Health Ecosystem: Extending Symptom Networks With Risk and Protective Factors. Frontiers in Psychiatry, 12, Article 640658. https://doi.org/10.3389/fpsyt.2021.640658 [details]
- Moriarity, D. P., Horn, S. R., Kautz, M. M., Haslbeck, J. M. B., & Alloy, L. B. (2021). How handling extreme C-reactive protein (CRP) values and regularization influences CRP and depression criteria associations in network analyses. Brain, behavior, and immunity, 91, 393-403. https://doi.org/10.1016/j.bbi.2020.10.020 [details]
- Robinaugh, D. J., Haslbeck, J. M. B., Ryan, O., Fried, E. I., & Waldorp, L. J. (2021). Invisible Hands and Fine Calipers: A Call to Use Formal Theory as a Toolkit for Theory Construction. Perspectives on Psychological Science, 16(4), 725-743. Advance online publication. https://doi.org/10.1177/1745691620974697 [details]
- Walentek, D., Broere, J., Cinelli, M., Dekker, M. M., & Haslbeck, J. M. B. (2021). Success of economic sanctions threats: coercion, information and commitment. International Interactions, 47(3), 417-448. https://doi.org/10.1080/03050629.2021.1860034 [details]
2020
- Dablander, F., Ryan, O., & Haslbeck, J. M. B. (2020). Choosing between AR(1) and VAR(1) Models in Typical Psychological Applications. PLoS ONE, 15(10), Article e0240730. https://doi.org/10.1371/journal.pone.0240730 [details]
- Fried, E. I., von Stockert, S., Haslbeck, J. M. B., Lamers, F., Schoevers, R. A., & Pennix, B. W. J. H. (2020). Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates. Psychological Medicine, 50(16), 2682-2690. https://doi.org/10.1017/S0033291719002770 [details]
- Haslbeck, J. M. B., & Waldorp, L. J. (2020). mgm: Structure Estimation for Time-Varying Mixed Graphical Models in high-dimensional Data. Journal of Statistical Software, 93, Article 8. https://doi.org/10.18637/jss.v093.i08 [details]
- Haslbeck, J. M. B., & Wulff, D. U. (2020). Estimating the Number of Clusters via Normalized Cluster Instability. Computational Statistics, 35(4), 1879–1894. https://doi.org/10.1007/s00180-020-00981-5 [details]
2019
- Dablander, F., Epskamp, S., & Haslbeck, J. M. B. (2019). Studying Statistics Anxiety Requires Sound Statistics: A Comment on Siew, McCartney, and Vitevitch (2019). Scholarship of Teaching and Learning in Psychology, 5(4), 319-323. https://doi.org/10.31234/osf.io/pfnys, https://doi.org/10.1037/stl0000159 [details]
- Kieslich, P. J., Henninger, F., Wulff, D. U., Haslbeck, J. M. B., & Schulte-Mecklenbeck, M. (2019). Mouse-Tracking: A Practical Guide to Implementation and Analysis. In M. Schulte-Mecklenbeck, A. Kühberger, & J. G. Johnson (Eds.), A Handbook of Process Tracing Methods (2nd ed., pp. 111-130). (The Society for Judgment and Decision Making Series). Routledge. https://doi.org/10.31234/osf.io/zuvqa, https://doi.org/10.4324/9781315160559-9 [details]
- Wulff, D. U., Haslbeck, J. M. B., Kieslich, P. J., Henninger, F., & Schulte-Mecklenbeck, M. (2019). Mouse-tracking: Detecting types in movement trajectories. In M. Schulte-Mecklenbeck, A. Kühberger, & J. J. Johnson (Eds.), A handbook of process tracing methods (2nd ed., pp. 131-145). Routledge. https://doi.org/10.4324/9781315160559-10 [details]
2018
- Haslbeck, J. M. B., & Waldorp, L. J. (2018). How well do network models predict observations? On the importance of predictability in network models. Behavior Research Methods, 50(2), 853-861. https://doi.org/10.3758/s13428-017-0910-x [details]
2017
- Haslbeck, J. M. B., & Fried, E. I. (2017). How predictable are symptoms in psychopathological networks? A reanalysis of 18 published datasets. Psychological Medicine, 47(16), 2767-2776. https://doi.org/10.1017/S0033291717001258 [details]
- Kossakowski, J. J., Groot, P., Haslbeck, J. M. B., Borsboom, D., & Wichers, M. (2017). Data from ‘Critical Slowing Down as a Personalized Early Warning Signal for Depression’. Journal of Open Psychology Data, 5(1). https://doi.org/10.5334/jopd.29 [details]
2024
- van Dongen, N., van Bork, R., Finnemann, A., Haslbeck, J. M. B., van der Maas, H. L. J., Robinaugh, D. J., de Ron, J., Sprenger, J., & Borsboom, D. (2024). Productive Explanation: A Framework for Evaluating Explanations in Psychological Science. PsyArXiv. https://doi.org/10.31234/osf.io/qd69g [details]
2023
- Vlaeyen, J. W. S., Haslbeck, J., Sjouwerman, R., & Peters, M. L. (2023). A reply to Manhapra. Pain, 164(3), e175-e176. https://doi.org/10.1097/j.pain.0000000000002833 [details]
2022
- Borsboom, D., Haslbeck, J. M. B., & Robinaugh, D. J. (2022). Systems-based approaches to mental disorders are the only game in town. World psychiatry, 21(3), 420-422. https://doi.org/10.1002/wps.21004 [details]
- Vlaeyen, J., Haslbeck, J. M. B., Sjouwerman, R., & Peters, M. L. (2022). Towards a dynamic account of chronic pain. Pain, 163(9), e1038-e1039. https://doi.org/10.1097/j.pain.0000000000002706 [details]
2016
- Haslbeck, J. M. B., Wood, G., & Witte, M. (2016). Temporal dynamics of number-space interaction in line bisection: Comment on Cleland and Bull (2015). Quarterly Journal of Experimental Psychology, 69(6), 1239-1242. https://doi.org/10.1080/17470218.2015.1095773 [details]
2015
- Haslbeck, J. M. B., & Waldorp, L. J. (2015). Structure estimation for mixed graphical models in high-dimensional data. ArXiv. http://arxiv.org/abs/1510.05677 [details]
2020
- Walentek, D., Broere, J., Cinelli, M., Dekker, M. & Haslbeck, J. (2020). Replication Data for: Success of Economic Sanctions Threats: Coercion, Information and Commitment. Harvard Dataverse. https://doi.org/10.7910/dvn/vqv40h
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Ernst, A. F., & Haslbeck, J. M. B. (2026). Modeling Qualitative Between-Person Heterogeneity in Time-Series using Latent Class Vector Autoregressive Models. Behavior Research Methods, 58(1), Article 28.