Submitted / under review

* shared first authorship

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

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

Haslbeck J. M. B., Borsboom D. & Waldorp L. J. (under review). Moderated Network Models. [arXiv]

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

Haslbeck J. M. B., Bringmann L. F., & Waldorp, L. J. (under review). How to estimate time-varying Vector Autoregressive Models? A comparison of two methods. [arXiv]

Haslbeck J. M. B., Wulff. D. U., (under review). Estimating the Number of Clusters via Normalized Cluster Instability. Journal of Computational and Graphical Statistics. [arXiv]

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

Haslbeck J. M. B., Waldorp L. J. (in preparation). Structure Estimation for Mixed Graphical models in High Dimensions. [arXiv]

In press

Kieslich, P. J., Henninger, F., Wulff, D. U., Haslbeck, J. M. B., & Schulte-Mecklenbeck, M. (in press). 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. (in press). 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]


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: [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]