* shared first authorship

Submitted / under review

Haslbeck, J. M. B. & van Bork, R. (submitted). Estimating the Number of Factors in Exploratory Factor Analysis via out-of-sample Prediction Errors. [PsyArXiv] [Github]

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. (submitted). Reporting Standards for Psychological Network Analyses in Cross-sectional Data [PsyArXiv]

Haslbeck J. M. B. (under review). Estimating Group Differences in Network Models using Moderation Analysis. [PsyArXiv]

Haslbeck J. M. B.*, Ryan O.*, & Dablander F.* (under review). The Sum of All Fears: Comparing Networks Based on Symptom Sum-Scores. [PsyArXiv]

Robinaugh, D. J., Haslbeck J. M. B., Waldorp, L. J., Kossakowski, J. J., Fried, E. I., Millner, A., McNally, R. J., van Nes, E. H., Scheffer, M., Kendler, K. S. & Borsboom, D. (under revision). Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder. [PsyArXiv]

Accepted / In press

Haslbeck J. M. B.*, Ryan O.*, Robinaugh D. J.*, Waldorp L. J., Borsboom D. (accepted). Modeling Psychopathology: From Data Models to Formal Theories. Psychological Methods. [PsyArXiv]

Haslbeck J. M. B.* & Ryan O.* (accepted). Recovering Within-Person Dynamics from Psychological Time Series. Multivariate Behavioral Research. [PsyArXiv]


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, 301. [Link]

Aalbers G., Engels T., Haslbeck J. M. B., Borsboom D. & Arntz A (2021). The Network Structure of Schema Modes. Clinical Psychology & Psychotherapy. [PsyArXiv] [Link]

Robinaugh, D., Haslbeck J. M. B., Ryan, O., Fried, E. I., & Waldorp, L. (2021). Invisible Hands and Fine Calipers: A Call to Use Formal Theory as a Toolkit for Theory Construction. Perspectives on Psychological Science. [PsyArXiv] [Link]

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 influences CRP and depression symptom networks: A replication and extension of Fried et al. (2019). Brain, Behavior and Immunity. [PsyArXiv]

Walentek, D., Broere, J., Cinelli, M, Dekker, M., & Haslbeck J. M. B. (2021). Success of Economic Sanctions Threats: Coercion, Information and Commitment. International Interactions. [Preprint]


Dablander F.*, Ryan O.* & Haslbeck J. M. B.* (2020). Choosing between AR(1) and VAR(1) Models in Typical Psychological Applications. PloS One. [PsyArXiv] [Link]

Haslbeck J. M. B. (2020). Modeling psychopathology: From data models to formal theories. (Doctoral Thesis) [Link]

Haslbeck J. M. B., Wulff. D. U., (2020). Estimating the Number of Clusters via Normalized Cluster Instability. Computational Statistics. [PDF] [arXiv]

Haslbeck J. M. B., Waldorp L. J. (2020). mgm: Structure Estimation for Time-Varying Mixed Graphical Models in high-dimensional Data. The Journal of Statistical Software. [arXiv] [Link]

Haslbeck J. M. B., Bringmann L. F., & Waldorp, L. J. (2020). A Tutorial on Estimating Time-Varying Vector Autoregressive Models. Multivariate Behavioral Research. [Link] [arXiv]

Haslbeck J. M. B., Epskamp S. & Marsman M., Waldorp L. J. (2020). Interpreting the Ising Model: The Input Matters. Multivariate Behavioral Research. [arXiv]


Haslbeck J. M. B., Borsboom D. & Waldorp L. J. (2019). Moderated Network Models. Multivariate Behavioral Research. [PDF] [arXiv]

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. New York, NY: Routledge. [PsyArXiv]

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. Kuehberger, & J. G. Johnson (Ed.), A handbook of process tracing methods (2. ed.). Psychology Press. [PsyArXiv]

Fried E. I., von Stockert S., Haslbeck J. M. B., Lamers F., Schoevers, R.A. & Pennix B. W. J. H. (2019). Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates. Psychological Medicine. [PDF] [OSF]

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. [PsyArXiv]


Haslbeck J. M. B., Waldorp L. J. (2018). How well do Network Models predict Future Observations? On the Importance of Predictability in Network Models. Behavior Research Methods. [PDF] [arXiv]


Haslbeck J. M. B., Fried E. I. (2017). How Predictable are Symptoms in Psychopathological Networks? A Reanalysis of 18 Published Datasets. Psychological Medicine. [PDF] [Supplement]

Kossakowski, J. J., Groot, P. C., 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, DOI: https://doi.org/10.5334/jopd.29. [PDF] [OSF]


Haslbeck J. M. B., Wood G., Witte M. (2015). Temporal dynamics of number-space interaction in line bisection: Comment on Cleland and Bull. Quarterly Journal of Experimental Psychology. [PDF, Experiment, Stimuli, Data, Code]