Papers

Submitted / under review

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

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. [PDF]

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

Published

Haslbeck J. M. B., Waldorp L. J. (2017). 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] [Data]

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]

Software

Stable

mgm: Estimation of Time-Varying Mixed Graphical Models [Github] [CRAN]

cstab: Selection of Number of Clusters via Resampled Normalized Cluster Stability [Github] [CRAN]

mousetrap: Functions for importing, preprocessing, analyzing, aggregating, and visualizing mouse-tracking data. [Github] [CRAN]

Under Development

Presentations

Haslbeck J.M.B. (2017). Predictability in Psychopathological Network Models. APS 2017, Boston, USA. [Slides]

Haslbeck J.M.B. (2017). Time-varying Mixed Graphical Models. Data Science Amsterdam Meetup, Amsterdam, Netherlands. [Slides]

Haslbeck J.M.B. (2017). Estimating Psychopathological Networks. Complex Systems Studies Workshop, Utrecht, Netherlands. [Slides Talk] [Workshop HTML] [Workshop Markdown]

Haslbeck J.M.B. (2017). Time-varying mixed graphical models. Psychoco 2017, Vienna, Austria. [Slides]

Haslbeck J.M.B. (2016). Time-varying mixed graphical models. [IOPS Winter Conference 2016, Groningen], The Netherlands. [Slides]

Haslbeck J.M.B. (2016). Time-varying mixed graphical models. Conference on Complex Systems 2016, Amsterdam, The Netherlands. [Slides]

Haslbeck J.M.B. (2016). Estimating time-varying mixed graphical models in high-dimensional data. COMPSTAT 2016, Oviedo, Spain. [Slides]

Haslbeck J.M.B. (2016). Estimating time-varying mixed graphical models in high-dimensional data. 5th VOC Conference, Tilburg University, The Netherlands. [Slides]

Haslbeck J.M.B. (2016). Workshop: Applying Network Analysis to Psychological Data. EFPSA Congress 2016, Vimeiro, Portugal. [Slides] [Code RMD] [Code HTML]

Haslbeck J.M.B. (2016). Understanding Mental Disorders as Complex Networks. EFPSA Congress 2016, Vimeiro, Portugal. [Slides]

Haslbeck J.M.B. (2016). Structure estimation for mixed graphical models in high-dimensional data. Psychoco 2016, University of Liège, Belgium. [Slides]

Haslbeck J.M.B. (2015). Structure estimation for mixed graphical models in high-dimensional data. EMPG 2015, University of Padua, Italy. [Slides]