Most papers are open access, or an earlier edition should be available at PsyArXiv or arXiv. If you can’t find an article, contact us.

Available data & R-scripts are linked inside square brackets.

A list of our publications can also be found on Google Scholar.

* indicates a preprint


Barnby, J. M., Haslbeck, J. M. B., Rosen, C., & Harrow, M. (2023). Modelling the Longitudinal Dynamics of Paranoia in Psychosis: A Temporal Network Analysis Over 20 Years. medRxiv.

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, 104266.

* Freichel, R. (2023). Symptom Network Analysis Tools for Applied Researchers with Cross-Sectional and Panel Data – A Brief Overview and Multiverse Analysis. PsyArXiv.

Freichel, R., Pfirrmann, J., Cousjin, J., de Jong, P., Franken, I., Banaschewski, T., Bokde, A. L. W., Desrivières, S., Flor, H., Grigis, A., Garavan, H., Heinz, A., Martinot, J.-L., Martinot, M.-L. P., Artiges, E., Nees, F., Orfanos, D. P., Poustka, L., Hohmann, S., … Consortium, I. (2023). Drinking motives, personality traits and life stressors—Identifying pathways to harmful alcohol use in adolescence using a panel network approach. Addiction.

* Gossage, L., Narayanan, A., Dipnall, J. F., Berk, M., Sumich, A., Haslbeck, J., Iusitini, L., Wrapson, W., Tautolo, E.-S., & Siegert, R. (2023). Understanding suicidality in Pacific adolescents in New Zealand using network analysis. PsyArXiv.

* Haslbeck, J., & Epskamp, S. (2023). Observed Correlations between Person-means Depend on Within-person Correlations. PsyArXiv.

* Haslbeck, J., Epskamp, S., & Waldorp, L. (2023). Testing for Group Differences in Multilevel Vector Autoregressive Models. PsyArXiv.

* Huth, K. B. S., de Ron, J., Goudriaan, A. E., Luigjes, J., Mohammadi, R., van Holst, R. J., Wagenmakers, E.-J., & Marsman, M. (2023). Bayesian analysis of cross-sectional networks: A tutorial in R and JASP. PsyArXiv.

* Marsman, M., & Haslbeck, J. (2023). Bayesian Analysis of the Ordinal Markov Random Field. PsyArXiv.

* Ryan, O., Dablander, F., & Haslbeck, J. (2023). Towards a Generative Model for Emotion Dynamics. PsyArXiv.

* Sekulovski, N., Keetelaar, S., Huth, K., Wagenmakers, E., van Bork, R., van den Bergh, D., & Marsman, M. (2023). Testing Conditional Independence in Psychometric Networks: An Analysis of Three Bayesian Methods.

Vlaeyen, J. W. S., Haslbeck, J., Sjouwerman, R., & Peters, M. L. (2023). Reply to Manhapra. PAIN, 164(3), e175.


Borsboom, D. (2022). Possible Futures for Network Psychometrics. Psychometrika, 87(1), 253–265.

Borsboom, D. (2022). Reflections on an emerging new science of mental disorders. Behaviour Research and Therapy, 156, 104127.

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.

Chambon, M., Dalege, J., Elberse, J. E., & van Harreveld, F. (2022). A Psychological Network Approach to Attitudes and Preventive Behaviors During Pandemics: A COVID-19 Study in the United Kingdom and the Netherlands. Social Psychological and Personality Science, 13(1), 233–245.

Chattrattrai, T., Blanken, T. F., Lobbezoo, F., Su, N., Aarab, G., & Van Someren, E. J. W. (2022). A network analysis of self-reported sleep bruxism in the Netherlands sleep registry: its associations with insomnia and several demographic, psychological, and life-style factors. Sleep Medicine, 93, 63-70.

* Claesen, A., Lakens, D., Vanpaemel, W., & van Dongen, N. (2022). Severity and Crises in Science: Are We Getting It Right When We’re Right and Wrong When We’re Wrong? PsyArXiv.

Dablander, F., Pichler, A., Cika, A., & Bacilieri, A. (2022). Anticipating critical transitions in psychological systems using early warning signals: Theoretical and practical considerations. Psychological Methods.

* Dekker, M., Walentek, D., Haslbeck, J., & Broere, J. (2022). Strategy Under Uncertainty: International Conflict and Variation in Information. APSA Preprints.

De Feijter, M., Kocevska, D., Blanken, T. F., van der Velpen, I. F., Ikram, M. A., & Luik, A. I. (2022). The network of psychosocial health in middle-aged and older adults during the first COVID-19 lockdown. Social Psychiatry and Psychiatric Epidemiology, 57(12), 2469–2479.

Epskamp, S., Isvoranu, A.-M., & Cheung, M. W.-L. (2022). Meta-analytic Gaussian Network Aggregation. Psychometrika, 87(1), 12–46.

Epskamp, S., van der Maas, H. L. J., Peterson, R. E., van Loo, H. M., Aggen, S. H., & Kendler, K. S. (2022). Intermediate stable states in substance use. Addictive Behaviors, 129, 107252.

Haslbeck, J. M. B. (2022). Estimating group differences in network models using moderation analysis. Behavior Research Methods, 54(1), 522–540.

Haslbeck, J. M. B., & Ryan, O. (2022). Recovering Within-Person Dynamics from Psychological Time Series. Multivariate Behavioral Research, 57(5), 735–766.

* Haslbeck, J., Ryan, O., & Dablander, F. (2022). Multimodality and Skewness in Emotion Time Series. PsyArXiv.

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.

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.

Henry, T. R., Robinaugh, D. J., & Fried, E. I. (2022). On the Control of Psychological Networks. Psychometrika, 87(1), 188–213.

Hoekstra, R. H. A., Epskamp, S., & Borsboom, D. (2022). Heterogeneity in Individual Network Analysis: Reality or Illusion? Multivariate Behavioral Research, 1–25.

Huth, K. B. S., Luigjes, J., Marsman, M., Goudriaan, A. E., & van Holst, R. J. (2022). Modeling alcohol use disorder as a set of interconnected symptoms – Assessing differences between clinical and population samples and across external factors. Addictive Behaviors, 125, 107128.

Huth, K. B. S., Waldorp, L. J., Luigjes, J., Goudriaan, A. E., van Holst, R. J., & Marsman, M. (2022). A Note on the Structural Change Test in Highly Parameterized Psychometric Models. Psychometrika, 87(3), 1064–1080.

* Huth, K., Zavlis, O., Luigjes, J., Galenkamp, H., Lok, A., Stronks, K., Bockting, C., Goudriaan, A., Marsman, M., & Holst, R. van. (2022). A Network Perspective on Ethnic, Religious, and Socioeconomic Factors in Alcohol Use—The HELIUS study. PsyArXiv.

Lancee, J., Harvey, A. G., Morin, C. M., Ivers, H., van der Zweerde, T., & Blanken, T. F. (2022). Network Intervention Analyses of cognitive therapy and behavior therapy for insomnia: Symptom specific effects and process measures. Behaviour Research and Therapy, 153, [104100].

Marsman, M., & Huth, K. (2022). Idiographic Ising and Divide and Color Models: Encompassing Networks for Heterogeneous Binary Data. Multivariate Behavioral Research, 0(0), 1–28.

Marsman, M., Huth, K., Waldorp, L. J., & Ntzoufras, I. (2022). Objective Bayesian Edge Screening and Structure Selection for Ising Networks. Psychometrika, 87(1), 47–82.

Marsman, M., & Rhemtulla, M. (2022). Guest Editors’ Introduction to The Special Issue “Network Psychometrics in Action”: Methodological Innovations Inspired by Empirical Problems. Psychometrika, 87(1), 1–11.

Marsman, M., Waldorp, L., & Borsboom, D. (2022). Towards an encompassing theory of network models: Reply to Brusco, Steinley, Hoffman, Davis-Stober, and Wasserman (2019). Psychological Methods, No Pagination Specified-No Pagination Specified.

Scheffer, M., Borsboom, D., Nieuwenhuis, S., & Westley, F. (2022). Belief traps: Tackling the inertia of harmful beliefs. Proceedings of the National Academy of Sciences, 119(32), e2203149119.

van Bork, R., Rhemtulla, M., Sijtsma, K., & Borsboom, D. (2022). A causal theory of error scores. Psychological Methods, No Pagination Specified-No Pagination Specified.

* van den Bergh, D., & Dablander, F. (2022). Flexible Bayesian Multiple Comparison Adjustment Using Dirichlet Process and Beta-Binomial Model Priors. arXiv.

* van Dongen, N., van Bork, R., Finnemann, A., van der Maas, H., Robinaugh, D., Haslbeck, J., de Ron, J., Sprenger, J., & Borsboom, D. (2022). Productive Explanation: A Framework for Evaluating Explanations in Psychological Science. PsyArXiv.

* van Dongen, N., Finnemann, A., de Ron, J., Tiokhin, L., Wang, S., Algermissen, J., Altmann, E. C., Chuang, L.-C., Dumbravă, A., Bahník, Š., Fuenderich, J., Geiger, S. J., Gerasimova, D., Golan, A., Herbers, J., Jekel, M., Lin, Y.-S., Moreau, D., Oberholzer, Y., … Borsboom, D. (2022). Many Modelers. PsyArXiv.

van Dongen, N., Sprenger, J., & Wagenmakers, E.-J. (2022). A Bayesian perspective on severity: Risky predictions and specific hypotheses. Psychonomic Bulletin & Review.

* van Ravenzwaaij, D., Bakker, M., Heesen, R., Romero, F., van Dongen, N., Crüwell, S., Field, S., Hartgerink, C. H. J., Held, L., Munafo, M., Pittelkow, M.-M., Tiokhin, L., Traag, V., van der Akker, O., van ’t Veer, A., & Wagenmakers, E.-J. (2022). Perspectives on Scientific Error. PsyArXiv.

Vlaeyen, J. W. S., Haslbeck, J. M. B., Sjouwerman, R., & Peters, M. L. (2022). Towards a dynamic account of chronic pain. PAIN, 163(9), e1038.

* Waldorp, L., & Haslbeck, J. (2022). Network Inference with the Lasso. PsyArXiv.

Waldorp, L., & Marsman, M. (2022). Relations between Networks, Regression, Partial Correlation, and the Latent Variable Model. Multivariate Behavioral Research, 57(6), 994–1006.


Aalbers, G., Engels, T., Haslbeck, J. M. B., Borsboom, D., & Arntz, A. (2021). The network structure of schema modes. Clinical Psychology & Psychotherapy, 28(5), 1065–1078.

Abend, R., Bajaj, M. A., Coppersmith, D. D. L., Kircanski, K., Haller, S. P., Cardinale, E. M., Salum, G. A., Wiers, R. W., Salemink, E., Pettit, J. W., Pérez-Edgar, K., Lebowitz, E. R., Silverman, W. K., Bar-Haim, Y., Brotman, M. A., Leibenluft, E., Fried, E. I., & Pine, D. S. (2021). A computational network perspective on pediatric anxiety symptoms. Psychological Medicine, 51(10), 1752–1762.

Aczel, B., Szaszi, B., Nilsonne, G., van den Akker, O. R., Albers, C. J., van Assen, M. A., Bastiaansen, J. A., Benjamin, D., Boehm, U., Botvinik-Nezer, R., Bringmann, L. F., Busch, N. A., Caruyer, E., Cataldo, A. M., Cowan, N., Delios, A., van Dongen, N. N., Donkin, C., van Doorn, J. B., … Wagenmakers, E.-J. (2021). Consensus-based guidance for conducting and reporting multi-analyst studies. ELife, 10, e72185.

Blanken, T. F., Bathelt, J., Deserno, M. K., Voge, L., Borsboom, D., & Douw, L. (2021). Connecting brain and behavior in clinical neuroscience: A network approach. Neuroscience and Biobehavioral Reviews, 130, 81-90.

Blanken, T. F., Jansson-Fröjmark, M., Sunnhed, R., & Lancee, J. (2021). Symptom-Specific Effects of Cognitive Therapy and Behavior Therapy for Insomnia: A Network Intervention Analysis. Journal of consulting and clinical psychology, 89(4), 364–370.

Borsboom, D., van der Maas, H. L. J., Dalege, J., Kievit, R. A., & Haig, B. D. (2021). Theory Construction Methodology: A Practical Framework for Building Theories in Psychology. Perspectives on Psychological Science, 16(4), 756–766.

Epskamp, S., Fried, E. I., van Borkulo, C. D., Robinaugh, D. J., Marsman, M., Dalege, J., Rhemtulla, M., & Cramer, A. O. J. (2021). Investigating the Utility of Fixed-margin Sampling in Network Psychometrics. Multivariate Behavioral Research, 56(2), 314–328.

Finnemann, A., Borsboom, D., Epskamp, S., & van der Maas, H. L. J. (2021). The Theoretical and Statistical Ising Model: A Practical Guide in R. Psych, 3(4), Article 4.

Fried, E. I., van Borkulo, C. D., & Epskamp, S. (2021). On the Importance of Estimating Parameter Uncertainty in Network Psychometrics: A Response to Forbes et al. (2019). Multivariate Behavioral Research, 56(2), 243–248.

Haslbeck, J. M. B., Borsboom, D., & Waldorp, L. J. (2021). Moderated Network Models. Multivariate Behavioral Research, 56(2), 256–287.

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.

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.

Hinze, V., Ford, T., Crane, C., Haslbeck, J. M. B., Hawton, K., Gjelsvik, B., Allwood, M., Aukland, L., Casey, T., De Wilde, K., Farley, E.-R., Fletcher, K., Kappelmann, N., Kuyken, Prof. W., Laws, S., Lord, L., Medlicott, E., Montero-Marin, Dr. J., Nuthall, E., … Wainman, B. (2021). Does depression moderate the relationship between pain and suicidality in adolescence? A moderated network analysis. Journal of Affective Disorders, 292, 667–677.

Isvoranu, A.-M., Epskamp, S., & Cheung, M. W.-L. (2021). Network models of posttraumatic stress disorder: A meta-analysis. Journal of Abnormal Psychology, 130(8), 841–861.

Liu, D., Epskamp, S., Isvoranu, A.-M., Chen, C., Liu, W., & Hong, X. (2021). Network analysis of physical and psychiatric symptoms of hospital discharged patients infected with COVID-19. Journal of Affective Disorders, 294, 707–713.

* Lunansky, G., Hoekstra, R. H. A., & Blanken, T. (2021). Disentangling dynamic affect trajectories for distinct depression courses during the COVID-19 pandemic. 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.

* Maier, M., van Dongen, N., & Borsboom, D. (2021). Comparing Theories with the Ising Model of Explanatory Coherence. PsyArXiv.

Moriarity, D. P., van Borkulo, C., & Alloy, L. B. (2021). Inflammatory phenotype of depression symptom structure: A network perspective. Brain, Behavior, and Immunity, 93, 35–42.

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.

Ron, J. de, Fried, E. I., & Epskamp, S. (2021). Psychological networks in clinical populations: Investigating the consequences of Berkson’s bias. Psychological Medicine, 51(1), 168–176.

Schumacher, L., Burger, J., Zoellner, F., Zindler, A., Epskamp, S., & Barthel, D. (2021). Using clinical expertise and empirical data in constructing networks of trauma symptoms in refugee youth. European Journal of Psychotraumatology, 12(1), 1920200.

van Bork, R., Rhemtulla, M., Waldorp, L. J., Kruis, J., Rezvanifar, S., & Borsboom, D. (2021). Latent Variable Models and Networks: Statistical Equivalence and Testability. Multivariate Behavioral Research, 56(2), 175–198.

* van Dongen, N., & van Grootel, L. (2021). Overview on the Null Hypothesis Significance Test. PsyArXiv.

Vervaet, M., Puttevils, L., Hoekstra, R. H. A., Fried, E., & Vanderhasselt, M.-A. (2021). Transdiagnostic vulnerability factors in eating disorders: A network analysis. European Eating Disorders Review, 29(1), 86–100.

Verwimp, C., Tijms, J., Snellings, P., Haslbeck, J. M. B., & Wiers, R. W. (2021). A network approach to dyslexia: Mapping the reading network. Development and Psychopathology, 1–15.

Vetter, J. S., Spiller, T. R., Cathomas, F., Robinaugh, D., Brühl, A., Boeker, H., Seifritz, E., & Kleim, B. (2021). Sex differences in depressive symptoms and their networks in a treatment-seeking population – a cross-sectional study. Journal of Affective Disorders, 278, 357–364.

Wagenmakers, E.-J., Sarafoglou, A., Aarts, S., Albers, C., Algermissen, J., Bahník, Š., van Dongen, N., Hoekstra, R., Moreau, D., van Ravenzwaaij, D., Sluga, A., Stanke, F., Tendeiro, J., & Aczel, B. (2021). Seven steps toward more transparency in statistical practice. Nature Human Behaviour, 5(11), Article 11.

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.


Blanken, T. F., Borsboom, D., Penninx, B. W., & Van Someren, E. J. (2020). Network outcome analysis identifies difficulty initiating sleep as a primary target for prevention of depression: A 6-year prospective study. Sleep, 43(5), zsz288.

Boyette, L.-L., Isvoranu, A.-M., Schirmbeck, F., Velthorst, E., Simons, C. J. P., Barrantes-Vidal, N., Bressan, R., Kempton, M. J., Krebs, M.-O., McGuire, P., Nelson, B., Nordentoft, M., Riecher-Rössler, A., Ruhrmann, S., Rutten, B. P., Sachs, G., Valmaggia, L. R., van der Gaag, M., Borsboom, D., … EU-GEI High Risk Study. (2020). From Speech Illusions to Onset of Psychotic Disorder: Applying Network Analysis to an Experimental Measure of Aberrant Experiences. Schizophrenia Bulletin Open, 1(1), sgaa025.

Burger, J., Stroebe, M. S., Perrig-Chiello, P., Schut, H. A., Spahni, S., Eisma, M. C., & Fried, E. I. (2020). Bereavement or breakup: Differences in networks of depression. Journal of Affective Disorders, 267, 1–8.

Burger, J., van der Veen, D. C., Robinaugh, D. J., Quax, R., Riese, H., Schoevers, R. A., & Epskamp, S. (2020). Bridging the gap between complexity science and clinical practice by formalizing idiographic theories: A computational model of functional analysis. BMC Medicine, 18(1), 99.

Cramer, A. O. J., Leertouwer, Ij., Lanius, R., & Frewen, P. (2020). A Network Approach to Studying the Associations Between Posttraumatic Stress Disorder Symptoms and Dissociative Experiences. Journal of Traumatic Stress, 33(1), 19–28.

* Dablander, F. (2020). An Introduction to Causal Inference. PsyArXiv.

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), e0240730.

de Mooij, S. M. M., Blanken, T. F., Grasman, R. P. P. P., Ramautar, J. R., Van Someren, E. J. W., & van der Maas, H. L. J. (2020). Dynamics of sleep: Exploring critical transitions and early warning signals. Computer Methods and Programs in Biomedicine, 193, 105448.

Djelantik, A. A. A. M. J., Robinaugh, D. J., Kleber, R. J., Smid, G. E., & Boelen, P. A. (2020). Symptomatology following loss and trauma: Latent class and network analyses of prolonged grief disorder, posttraumatic stress disorder, and depression in a treatment-seeking trauma-exposed sample. Depression and Anxiety, 37(1), 26–34.

Epskamp, S. (2020). Psychometric network models from time-series and panel data. Psychometrika, 85(1), 206–231.

Fried, E. I., Stockert, S. von, Haslbeck, J. M. B., Lamers, F., Schoevers, R. A., & Penninx, 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.

Greene, T., Gelkopf, M., Fried, E. I., Robinaugh, D. J., & Lapid Pickman, L. (2020). Dynamic Network Analysis of Negative Emotions and DSM-5 Posttraumatic Stress Disorder Symptom Clusters During Conflict. Journal of Traumatic Stress, 33(1), 72–83.

Hakulinen, C., Fried, E. I., Pulkki-Råback, L., Virtanen, M., Suvisaari, J., & Elovainio, M. (2020). Network structure of depression symptomology in participants with and without depressive disorder: The population-based Health 2000–2011 study. Social Psychiatry and Psychiatric Epidemiology, 55(10), 1273–1282.

Haslbeck, J. M. B., & Waldorp, L. J. (2020). mgm: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data. Journal of Statistical Software, 93, 1–46.

Haslbeck, J. M. B., & Wulff, D. U. (2020). Estimating the number of clusters via a corrected clustering instability. Computational Statistics, 35(4).

Hilland, E., Landrø, N. I., Kraft, B., Tamnes, C. K., Fried, E. I., Maglanoc, L. A., & Jonassen, R. (2020). Exploring the links between specific depression symptoms and brain structure: A network study. Psychiatry and Clinical Neurosciences, 74(3), 220–221.

Hirota, T., Deserno, M., & McElroy, E. (2020). The Network Structure of Irritability and Aggression in Individuals with Autism Spectrum Disorder. Journal of Autism and Developmental Disorders, 50(4), 1210–1220.

Isvoranu, A.-M., Guloksuz, S., Epskamp, S., van Os, J., Borsboom, D., & Investigators, G. (2020). Toward incorporating genetic risk scores into symptom networks of psychosis. Psychological Medicine, 50(4), 636–643.

Jongeneel, A., Aalbers, G., Bell, I., Fried, E. I., Delespaul, P., Riper, H., van der Gaag, M., & van den Berg, D. (2020). A time-series network approach to auditory verbal hallucinations: Examining dynamic interactions using experience sampling methodology. Schizophrenia Research, 215, 148–156.

Kalis, A., & Borsboom, D. (2020). Folk psychology as a causal language. Theory & Psychology, 30(5), 723–728.

Kan, K.-J., de Jonge, H., van der Maas, H. L. J., Levine, S. Z., & Epskamp, S. (2020). How to Compare Psychometric Factor and Network Models. Journal of Intelligence, 8(4), Article 4.

Kruis, J., Maris, G., Marsman, M., Bolsinova, M., & van der Maas, H. L. J. (2020). Deviations of rational choice: An integrative explanation of the endowment and several context effects. Scientific Reports, 10(1), Article 1.

Lange, J., Dalege, J., Borsboom, D., van Kleef, G. A., & Fischer, A. H. (2020). Toward an Integrative Psychometric Model of Emotions. Perspectives on Psychological Science, 15(2), 444–468.

* Leising, D., Burger, J., Zimmermann, J., Bäckström, M., Oltmanns, J. R., & Connelly, B. S. (2020). Why do items correlate with one another? A conceptual analysis with relevance for general factors and network models. PsyArXiv.

Lin, S.-Y., Fried, E. I., & Eaton, N. R. (2020). The association of life stress with substance use symptoms: A network analysis and replication. Journal of Abnormal Psychology, 129, 204–214.

Lunansky, G., van Borkulo, C., & Borsboom, D. (2020). Personality, Resilience, and Psychopathology: A Model for the Interaction between Slow and Fast Network Processes in the Context of Mental Health. European Journal of Personality, 34(6), 969–987.

Meier, M., Kossakowski, J. J., Jones, P. J., Kay, B., Riemann, B. C., & McNally, R. J. (2020). Obsessive–compulsive symptoms in eating disorders: A network investigation. International Journal of Eating Disorders, 53(3), 362–371.

Miers, A. C., Weeda, W. D., Blöte, A. W., Cramer, A. O. J., Borsboom, D., & Westenberg, P. M. (2020). A cross-sectional and longitudinal network analysis approach to understanding connections among social anxiety components in youth. Journal of Abnormal Psychology, 129, 82–91.

Morvan, Y., Fried, E. I., & Chevance, A. (2020). Network modeling in psychopathology: Hopes and challenges. L’Encéphale, 46(1), 1–2.

Robinaugh, D. J., Hoekstra, R. H. A., Toner, E. R., & Borsboom, D. (2020). The network approach to psychopathology: A review of the literature 2008–2018 and an agenda for future research. Psychological Medicine, 50(3), 353–366.

Sachisthal, M. S. M., Jansen, B. R. J., Dalege, J., & Raijmakers, M. E. J. (2020). Relating teenagers’ science interest network characteristics to later science course enrolment: An analysis of Australian PISA 2006 and Longitudinal Surveys of Australian Youth data. Australian Journal of Education, 64(3), 264–281.

See, A. Y., Klimstra, T. A., Cramer, A. O. J., & Denissen, J. J. A. (2020). The Network Structure of Personality Pathology in Adolescence With the 100-Item Personality Inventory for DSM-5 Short-Form (PID-5-SF). Frontiers in Psychology, 11.

Tio, P., Waldorp, L., & Van Deun, K. (2020). Constructing Graphical Models for Multi-Source Data: Sparse Network and Component Analysis. In T. Imaizumi, A. Okada, S. Miyamoto, F. Sakaori, Y. Yamamoto, & M. Vichi (Eds.), Advanced Studies in Classification and Data Science (pp. 275–287). Springer.

van den Berg, J. W., Smid, W., Kossakowski, J. J., van Beek, D., Borsboom, D., Janssen, E., & Gijs, L. (2020). The Application of Network Analysis to Dynamic Risk Factors in Adult Male Sex Offenders. Clinical Psychological Science, 8(3), 539–554.

van der Maas, H. L. J., Dalege, J., & Waldorp, L. (2020). The polarization within and across individuals: The hierarchical Ising opinion model. Journal of Complex Networks, 8(2), cnaa010.

van Heijst, B. F., Deserno, M. K., Rhebergen, D., & Geurts, H. M. (2020). Autism and depression are connected: A report of two complimentary network studies. Autism, 24(3), 680–692.

Waldorp, L., & Kossakowski, J. (2020). Mean field dynamics of stochastic cellular automata for random and small-world graphs. Journal of Mathematical Psychology, 97, 102380.

Ziermans, T., Isvoranu, A.-M., Schirmbeck, F., Geurts, H., & De Haan, L. (2020). M83. Autistic Traits as Linking Pin to Social Functioning in Psychosis: A Network Approach. Schizophrenia Bulletin, 46(Suppl 1), S166.

Zwicker, M. V., Nohlen, H. U., Dalege, J., Gruter, G.-J. M., & van Harreveld, F. (2020). Applying an attitude network approach to consumer behaviour towards plastic. Journal of Environmental Psychology, 69, 101433.


Abacioglu, C. S., Isvoranu, A.-M., Verkuyten, M., Thijs, J., & Epskamp, S. (2019). Exploring multicultural classroom dynamics: A network analysis. Journal of School Psychology, 74, 90–105.

Barbalat, G., van den Bergh, D., & Kossakowski, J. J. (2019). Outcome measurement in mental health services: Insights from symptom networks. BMC Psychiatry, 19(1), 202.

Blanken, T. F., Benjamins, J. S., Borsboom, D., Vermunt, J. K., Paquola, C., Ramautar, J., Dekker, K., Stoffers, D., Wassing, R., Wei, Y., & Van Someren, E. J. W. (2019). Insomnia disorder subtypes derived from life history and traits of affect and personality. The Lancet Psychiatry, 6(2), 151–163.

Blanken, T. F., Van Der Zweerde, T., Van Straten, A., Van Someren, E. J. W., Borsboom, D., & Lancee, J. (2019). Introducing Network Intervention Analysis to Investigate Sequential, Symptom-Specific Treatment Effects: A Demonstration in Co-Occurring Insomnia and Depression. Psychotherapy and Psychosomatics, 88(1), 52–54.

Borsboom, D., Cramer, A. O. J., & Kalis, A. (2019). Brain disorders? Not really: Why network structures block reductionism in psychopathology research. Behavioral and Brain Sciences, 42, e2.

Borsboom, D., Cramer, A. O. J., & Kalis, A. (2019). Reductionism in retreat. Behavioral and Brain Sciences, 42, e32.

Bringmann, L. F., Elmer, T., Epskamp, S., Krause, R. W., Schoch, D., Wichers, M., Wigman, J. T. W., & Snippe, E. (2019). What do centrality measures measure in psychological networks? Journal of Abnormal Psychology, 128(8), 892–903.

Costantini, G., Richetin, J., Preti, E., Casini, E., Epskamp, S., & Perugini, M. (2019). Stability and variability of personality networks. A tutorial on recent developments in network psychometrics. Personality and Individual Differences, 136, 68–78.

* Dablander, F., Epskamp, S., & Haslbeck, J. (2019). Studying Statistics Anxiety Requires Sound Statistics: A Comment on Siew, McCartney, and Vitevitch (2019). PsyArXiv.

Dablander, F., & Hinne, M. (2019). Node centrality measures are a poor substitute for causal inference. Scientific Reports, 9(1), Article 1.

Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. J. (2019). A Network Perspective on Attitude Strength: Testing the Connectivity Hypothesis. Social Psychological and Personality Science, 10(6), 746–756.

Fritz, J., Stochl, J., Fried, E. I., Goodyer, I. M., van Borkulo, C. D., Wilkinson, P. O., & van Harmelen, A.-L. (2019). Unravelling the complex nature of resilience factors and their changes between early and later adolescence. BMC Medicine, 17(1), 203.

Kalisch, R., Cramer, A. O. J., Binder, H., Fritz, J., Leertouwer, Ij., Lunansky, G., Meyer, B., Timmer, J., Veer, I. M., & van Harmelen, A.-L. (2019). Deconstructing and Reconstructing Resilience: A Dynamic Network Approach. Perspectives on Psychological Science, 14(5), 765–777.

* Kossakowski, J., Oudheusden, L. J. B., McNally, R. J., Riemann, B. C., Waldorp, L., & van der Maas, H. L. J. (2019). Introducing the Causal Graph Approach to Psychopathology: An Illustration in Patients with Obsessive-Compulsive Disorder. PsyArXiv.

* Kruis, J., Maris, G., Marsman, M., Molenaar, D., Bolsinova, M., & van der Maas, H. L. J. (2019). The physics of (ir)rational choice (arXiv:1904.08975). arXiv.

Letina, S., Blanken, T. F., Deserno, M. K., & Borsboom, D. (2019). Expanding Network Analysis Tools in Psychological Networks: Minimal Spanning Trees, Participation Coefficients, and Motif Analysis Applied to a Network of 26 Psychological Attributes. Complexity, 2019, e9424605.

Marsman, M., Sigurdardóttir, H., Bolsinova, M., & Maris, G. (2019). Characterizing the Manifest Probability Distributions of Three Latent Trait Models for Accuracy and Response Time. Psychometrika, 84(3), 870–891.

Marsman, M., Tanis, C. C., Bechger, T. M., & Waldorp, L. J. (2019). Network Psychometrics in Educational Practice. In B. P. Veldkamp & C. Sluijter (Eds.), Theoretical and Practical Advances in Computer-based Educational Measurement (pp. 93–120). Springer International Publishing.

Oreel, T. H., Borsboom, D., Epskamp, S., Hartog, I. D., Netjes, J. E., Nieuwkerk, P. T., Henriques, J. P. S., Scherer-Rath, M., van Laarhoven, H. W. M., & Sprangers, M. A. G. (2019). The dynamics in health-related quality of life of patients with stable coronary artery disease were revealed: A network analysis. Journal of Clinical Epidemiology, 107, 116–123.

Ou, L., Hofman, A. D., Simmering, V. R., Bechger, T., Maris, G., & van der Maas, H. L. J. (2019). Modeling Person-Specific Development of Math Skills in Continuous Time: New Evidence for Mutualism. In International Educational Data Mining Society. International Educational Data Mining Society.

* Robinaugh, D., Haslbeck, J., Waldorp, L., Kossakowski, J., Fried, E. I., Millner, A., McNally, R. J., Ryan, O., Ron, J. de, van der Maas, H., van Nes, E. H., Scheffer, M., Kendler, K. S., & Borsboom, D. (2019). Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder. PsyArXiv.

Sachisthal, M. S. M., Jansen, B. R. J., Peetsma, T. T. D., Dalege, J., van der Maas, H. L. J., & Raijmakers, M. E. J. (2019). Introducing a science interest network model to reveal country differences. Journal of Educational Psychology, 111, 1063–1080.

Savi, A. O., Marsman, M., van der Maas, H. L. J., & Maris, G. K. J. (2019). The Wiring of Intelligence. Perspectives on Psychological Science, 14(6), 1034–1061.

Sayans-Jiménez, P., van Harreveld, F., Dalege, J., & Rojas Tejada, A. J. (2019). Investigating stereotype structure with empirical network models. European Journal of Social Psychology, 49(3), 604–621.

van Borkulo, C., Wichers, M., Boschloo, L., Epskamp, S., Schoevers, R., Kamphuis, J., Borsboom, D., & Waldorp, L. (2019). The Contact Process as a Model for Predicting Network Dynamics of Psychopathology.

van der Maas, H. L. J., Savi, A. O., Hofman, A., Kan, K.-J., & Marsman, M. (2019). The network approach to general intelligence. In General and specific mental abilities (pp. 108–131). Cambridge Scholars Publishing.

van Wanrooij, L. L., Borsboom, D., van Charante, E. P. M., Richard, E., & van Gool, W. A. (2019). A network approach on the relation between apathy and depression symptoms with dementia and functional disability. International Psychogeriatrics, 31(11), 1655–1663.

Waldorp, L., Marsman, M., & Maris, G. (2019). Logistic regression and Ising networks: Prediction and estimation when violating lasso assumptions. Behaviormetrika, 46(1), 49–72.


Blanken, T. F., Deserno, M. K., Dalege, J., Borsboom, D., Blanken, P., Kerkhof, G. A., & Cramer, A. O. J. (2018). The role of stabilizing and communicating symptoms given overlapping communities in psychopathology networks. Scientific Reports, 8(1), Article 1.

Borsboom, D., Robinaugh, D. J., Group, T. P., Rhemtulla, M., & Cramer, A. O. J. (2018). Robustness and replicability of psychopathology networks. World Psychiatry, 17(2), 143–144.

Bos, F. M., Fried, E. I., Hollon, S. D., Bringmann, L. F., Dimidjian, S., DeRubeis, R. J., & Bockting, C. L. H. (2018). Cross-sectional networks of depressive symptoms before and after antidepressant medication treatment. Social Psychiatry and Psychiatric Epidemiology, 53(6), 617–627. [R-script]

Briganti, G., Kempenaers, C., Braun, S., Fried, E. I., & Linkowski, P. (2018). Network analysis of empathy items from the interpersonal reactivity index in 1973 young adults. Psychiatry Research, 265, 87–92. [Data] [R-script]

Bringmann, L. F., & Eronen, M. I. (2018). Don’t blame the model: Reconsidering the network approach to psychopathology. Psychological Review, 125, 606–615.

Bringmann, L. F., Ferrer, E., Hamaker, E. L., Borsboom, D., & Tuerlinckx, F. (2018). Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model. Multivariate Behavioral Research, 53(3), 293–314.

Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. J. (2018). The Attitudinal Entropy (AE) Framework as a General Theory of Individual Attitudes. Psychological Inquiry, 29(4), 175–193.

Derks, K., Burger, J., van Doorn, J., Kossakowski, J. J., Matzke, D., Atticciati, L., Beitner, J., Benzesin, V., Bruijn, A. L. de, Cohen, T. R. H., Cordesius, E. P. A., van Dekken, M., Delvendahl, N., Dobbelaar, S., Groenendijk, E. R., Hermans, M. E., Hiekkaranta, A. P., Hoekstra, R. H. A., Hoffmann, A. M., … Wagenmakers, E.-J. (2018). Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance. Journal of European Psychology Students, 9(1), Article 1.

Deserno, M. K., Borsboom, D., Begeer, S., & Geurts, H. M. (2018). Relating ASD symptoms to well-being: Moving across different construct levels. Psychological Medicine, 48(7), 1179–1189.

Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212.

Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial correlation networks. Psychological Methods, 23, 617–634.

Epskamp, S., Maris, G. K. J., Waldorp, L. J., & Borsboom, D. (2018). Network Psychometrics (arXiv:1609.02818). arXiv.

Epskamp, S., van Borkulo, C. D., van der Veen, D. C., Servaas, M. N., Isvoranu, A.-M., Riese, H., & Cramer, A. O. J. (2018). Personalized Network Modeling in Psychopathology: The Importance of Contemporaneous and Temporal Connections. Clinical Psychological Science, 6(3), 416–427.

Epskamp, S., Waldorp, L. J., Mõttus, R., & Borsboom, D. (2018). The Gaussian Graphical Model in Cross-Sectional and Time-Series Data. Multivariate Behavioral Research, 53(4), 453–480.

Fonseca-Pedrero, E., Ortuño, J., Debbané, M., Chan, R. C. K., Cicero, D., Zhang, L. C., Brenner, C., Barkus, E., Linscott, R. J., Kwapil, T., Barrantes-Vidal, N., Cohen, A., Raine, A., Compton, M. T., Tone, E. B., Suhr, J., Inchausti, F., Bobes, J., Fumero, A., … Fried, E. I. (2018). The Network Structure of Schizotypal Personality Traits. Schizophrenia Bulletin, 44(suppl_2), S468–S479.

Fried, E. I., Eidhof, M. B., Palic, S., Costantini, G., Huisman-van Dijk, H. M., Bockting, C. L. H., Engelhard, I., Armour, C., Nielsen, A. B. S., & Karstoft, K.-I. (2018). Replicability and Generalizability of Posttraumatic Stress Disorder (PTSD) Networks: A Cross-Cultural Multisite Study of PTSD Symptoms in Four Trauma Patient Samples. Clinical Psychological Science, 6(3), 335–351.

Fritz, J., Fried, E. I., Goodyer, I. M., Wilkinson, P. O., & van Harmelen, A.-L. (2018). A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity. Scientific Reports, 8(1), Article 1.

Greene, T., Gelkopf, M., Epskamp, S., & Fried, E. (2018). Dynamic networks of PTSD symptoms during conflict. Psychological Medicine, 48(14), 2409–2417.

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.

Hoekstra, R. H., Kossakowski, J. J., & van der Maas, H. L. (2018). Psychological perturbation data on attitudes towards the consumption of meat. Journal of Open Psychology Data6(1).

Kendler, K. S., Aggen, S. H., Flint, J., Borsboom, D., & Fried, E. I. (2018). The centrality of DSM and non-DSM depressive symptoms in Han Chinese women with major depression. Journal of Affective Disorders, 227, 739–744.

* Kossakowski, J. J., Gordijn, M. C., Riese, H., & Waldorp, L. J. (2018). Mean Field Dynamics of Graphs II: Assessing the Risk for the Development of Phase Transitions in Empirical Data (arXiv:1610.05046). arXiv.

Marsman, M., Borsboom, D., Kruis, J., Epskamp, S., van Bork, R., Waldorp, L. J., van der Maas, H. L. J., & Maris, G. (2018). An Introduction to Network Psychometrics: Relating Ising Network Models to Item Response Theory Models. Multivariate Behavioral Research, 53(1), 15–35.

Murphy, J., McBride, O., Fried, E., & Shevlin, M. (2018). Distress, Impairment and the Extended Psychosis Phenotype: A Network Analysis of Psychotic Experiences in an US General Population Sample. Schizophrenia Bulletin, 44(4), 768–777.

Rouquette, A., Pingault, J.-B., Fried, E. I., Orri, M., Falissard, B., Kossakowski, J. J., Vitaro, F., Tremblay, R., Cote, S. M., & Borsboom, D. (2018). Emotional and Behavioral Symptom Network Structure in Elementary School Girls and Association With Anxiety Disorders and Depression in Adolescence and Early Adulthood: A Network Analysis. JAMA Psychiatry, 75(11), 1173–1181.

Santos, H. P. J., Kossakowski, J. J., Schwartz, T. A., Beeber, L., & Fried, E. I. (2018). Longitudinal network structure of depression symptoms and self-efficacy in low-income mothers. PLOS ONE, 13(1), e0191675.

Scheffer, M., Bolhuis, J. E., Borsboom, D., Buchman, T. G., Gijzel, S. M. W., Goulson, D., Kammenga, J. E., Kemp, B., van de Leemput, I. A., Levin, S., Martin, C. M., Melis, R. J. F., van Nes, E. H., Romero, L. M., & Olde Rikkert, M. G. M. (2018). Quantifying resilience of humans and other animals. Proceedings of the National Academy of Sciences, 115(47), 11883–11890.

Schweren, L., van Borkulo, C. D., Fried, E., & Goodyer, I. M. (2018). Assessment of Symptom Network Density as a Prognostic Marker of Treatment Response in Adolescent Depression. JAMA Psychiatry, 75(1), 98–100.

van Bork, R., van Borkulo, C. D., Waldorp, L. J., Cramer, A. O. J., & Borsboom, D. (2018). Network Models for Clinical Psychology. In Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience (pp. 1–35). John Wiley & Sons, Ltd.

van Loo, H. M., Van Borkulo, C. D., Peterson, R. E., Fried, E. I., Aggen, S. H., Borsboom, D., & Kendler, K. S. (2018). Robust symptom networks in recurrent major depression across different levels of genetic and environmental risk. Journal of Affective Disorders, 227, 313–322.

van Rooijen, G., Isvoranu, A.-M., Kruijt, O. H., van Borkulo, C. D., Meijer, C. J., Wigman, J. T. W., Ruhé, H. G., de Haan, L., Bruggeman, R., Cahn, W., de Haan, L., Kahn, R. S., Meijer, C., Myin-Germeys, I., van Os, J., & Bartels-Velthuis, A. A. (2018). A state-independent network of depressive, negative and positive symptoms in male patients with schizophrenia spectrum disorders. Schizophrenia Research, 193, 232–239. [R-script in supplements]

Verschuere, B., van Ghesel Grothe, S., Waldorp, L., Watts, A. L., Lilienfeld, S. O., Edens, J. F., Skeem, J. L., & Noordhof, A. (2018). What features of psychopathy might be central? A network analysis of the Psychopathy Checklist-Revised (PCL-R) in three large samples. Journal of Abnormal Psychology, 127(1), 51–65.

von Stockert, S. H. H., Fried, E. I., Armour, C., & Pietrzak, R. H. (2018). Evaluating the stability of DSM-5 PTSD symptom network structure in a national sample of U.S. military veterans. Journal of Affective Disorders, 229, 63–68.

Werner, M., Štulhofer, A., Waldorp, L., & Jurin, T. (2018). A Network Approach to Hypersexuality: Insights and Clinical Implications. The Journal of Sexual Medicine, 15(3), 373–386.


Armour, C., Fried, E. I., Deserno, M. K., Tsai, J., & Pietrzak, R. H. (2017). A network analysis of DSM-5 posttraumatic stress disorder symptoms and correlates in U.S. military veterans. Journal of Anxiety Disorders, 45, 49–59.

Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry: Official Journal of the World Psychiatric Association (WPA), 16(1), 5–13.

Borsboom, D., Fried, E. I., Epskamp, S., Waldorp, L., van Borkulo, C. D., van der Maas, H., & Cramer, A. (2017). Pre-print: False alarm? A comprehensive reanalysis of “Evidence that psychopathology symptom networks have limited replicability” by Forbes, Wright, Markon, and Krueger.

Borsboom, D., & Wijsen, L. D. (2017). Psychology’s atomic bomb. Assessment in Education: Principles, Policy & Practice, 24(3), 440–446.

Bringmann, L. F., Hamaker, E. L., Vigo, D. E., Aubert, A., Borsboom, D., & Tuerlinckx, F. (2017). Changing dynamics: Time-varying autoregressive models using generalized additive modeling. Psychological Methods, 22(3), 409–425.

Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. J. (2017). Network Analysis on Attitudes: A Brief Tutorial. Social Psychological and Personality Science, 8(5), 528–537.

Dalege, J., Borsboom, D., van Harreveld, F., Waldorp, L. J., & van der Maas, H. L. J. (2017). Network Structure Explains the Impact of Attitudes on Voting Decisions. Scientific Reports, 7(1), Article 1.

de Beurs, D. P., van Borkulo, C. D., & O’Connor, R. C. (2017). Association between suicidal symptoms and repeat suicidal behaviour within a sample of hospital-treated suicide attempters. BJPsych Open, 3(3), 120–126.

Dejonckheere, E., Bastian, B., Fried, E. I., Murphy, S. C., & Kuppens, P. (2017). Perceiving social pressure not to feel negative predicts depressive symptoms in daily life. Depression and Anxiety, 34(9), 836–844.

Deserno, M. K., Borsboom, D., Begeer, S., & Geurts, H. M. (2017). Multicausal systems ask for multicausal approaches: A network perspective on subjective well-being in individuals with autism spectrum disorder. Autism: The International Journal of Research and Practice, 21(8), 960–971.

Epskamp, S., Kruis, J., & Marsman, M. (2017). Estimating psychopathological networks: Be careful what you wish for. PLOS ONE, 12(6), e0179891.

Epskamp, S., Rhemtulla, M., & Borsboom, D. (2017). Generalized Network Psychometrics: Combining Network and Latent Variable Models. Psychometrika, 82(4), 904–927.

Fried, E. (2017). Moving forward: How depression heterogeneity hinders progress in treatment and research. Expert Review of Neurotherapeutics, 17(5), 423–425.

Fried, E. I. (2017). Psychopathological Networks. In A. E. Wenzel (Ed.), The SAGE encyclopedia of abnormal and clinical psychology. New York, NY: SAGE Publications.

Fried, E. I. (2017). The 52 symptoms of major depression: Lack of content overlap among seven common depression scales. Journal of Affective Disorders, 208, 191–197.

Fried, E. I. (2017). What are psychological constructs? On the nature and statistical modelling of emotions, intelligence, personality traits and mental disorders. Health Psychology Review, 11(2), 130–134.

Fried, E. I., & Cramer, A. O. J. (2017). Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology. Perspectives on Psychological Science: A Journal of the Association for Psychological Science, 12(6), 999–1020.

Fried, E. I., van Borkulo, C. D., Cramer, A. O. J., Boschloo, L., Schoevers, R. A., & Borsboom, D. (2017). Mental disorders as networks of problems: A review of recent insights. Social Psychiatry and Psychiatric Epidemiology, 52(1), 1–10.

Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLOS ONE, 12(6), e0174035.

Heino, M. T. J., Fried, E. I., & LeBel, E. P. (2017). Commentary: Reproducibility in Psychological Science: When Do Psychological Phenomena Exist? Frontiers in Psychology, 8.

Isvoranu, A.-M., Boyette, L.-L., Guloksuz, S., & Borsboom, D. (2017). Symptom Network Models of Psychosis. PsyArXiv.

Isvoranu, A.-M., van Borkulo, C. D., Boyette, L.-L., Wigman, J. T. W., Vinkers, C. H., Borsboom, D., & Group Investigators. (2017). A Network Approach to Psychosis: Pathways Between Childhood Trauma and Psychotic Symptoms. Schizophrenia Bulletin, 43(1), 187–196.

Kroeze, R., van der Veen, D. C., Servaas, M. N., Bastiaansen, J. A., Oude Voshaar, R. C., Borsboom, D., Ruhe, H. G., Schoevers, R. A., & Riese, H. (2017). Personalized Feedback on Symptom Dynamics of Psychopathology: A Proof-of-Principle Study. Journal for Person-Oriented Research, 3(1), 1–10.

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, [Data]

Miloyan, B., & Fried, E. (2017). A reassessment of the relationship between depression and all-cause mortality in 3,604,005 participants from 293 studies. World Psychiatry, 16(2), 219–220.

Rhemtulla, M., Borsboom, D., & van Bork, R. (2017). How to Measure Nothing. Measurement: Interdisciplinary Research and Perspectives, 15(2), 95–97.

Santos, H., Fried, E. I., Asafu-Adjei, J., & Ruiz, R. J. (2017). Network Structure of Perinatal Depressive Symptoms in Latinas: Relationship to Stress and Reproductive Biomarkers. Research in Nursing & Health, 40(3), 218–228.

van Bork, R., Epskamp, S., Rhemtulla, M., Borsboom, D., & van der Maas, H. L. J. (2017). What is the p-factor of psychopathology? Some risks of general factor modeling. Theory & Psychology, 27(6), 759–773.

van Rooijen, G., Isvoranu, A.-M., Meijer, C. J., van Borkulo, C. D., Ruhé, H. G., & de Haan, L. (2017). A symptom network structure of the psychosis spectrum. Schizophrenia Research, 189, 75–83.

* Waldorp, L. J., & Kossakowski, J. J. (2017). Mean field dynamics of graphs I: Evolution of probabilistic cellular automata for random and small-world graphs (arXiv:1610.05105). arXiv.


Borsboom, D., Rhemtulla, M., Cramer, A. O. J., van der Maas, H. L. J., Scheffer, M., & Dolan, C. V. (2016). Kinds versus continua: A review of psychometric approaches to uncover the structure of psychiatric constructs. Psychological Medicine, 46(8), 1567–1579.

Boschloo, L., van Borkulo, C. D., Borsboom, D., & Schoevers, R. A. (2016). A Prospective Study on How Symptoms in a Network Predict the Onset of Depression. Psychotherapy and Psychosomatics, 85(3), 183–184.

Boschloo, L., Schoevers, R. A., van Borkulo, C. D., Borsboom, D., & Oldehinkel, A. J. (2016). The network structure of psychopathology in a community sample of preadolescents. Journal of Abnormal Psychology, 125, 599–606.

Bringmann, L. F., Pe, M. L., Vissers, N., Ceulemans, E., Borsboom, D., Vanpaemel, W., Tuerlinckx, F., & Kuppens, P. (2016). Assessing Temporal Emotion Dynamics Using Networks. Assessment, 23(4), 425–435.

Cramer, A. O. J., van Borkulo, C. D., Giltay, E. J., van der Maas, H. L. J., Kendler, K. S., Scheffer, M., & Borsboom, D. (2016). Major Depression as a Complex Dynamic System. PLOS ONE, 11(12), e0167490.

Dalege, J., Borsboom, D., van Harreveld, F., van den Berg, H., Conner, M., & van der Maas, H. L. J. (2016). Toward a formalized account of attitudes: The Causal Attitude Network (CAN) model. Psychological Review, 123, 2–22. [R-script]

Fried, E. I., Epskamp, S., Nesse, R. M., Tuerlinckx, F., & Borsboom, D. (2016). What are ‘good’ depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. Journal of Affective Disorders, 189, 314–320. [R-script]

Fried, E. I., van Borkulo, C. D., Epskamp, S., Schoevers, R. A., Tuerlinckx, F., & Borsboom, D. (2016). Measuring depression over time . . . Or not? Lack of unidimensionality and longitudinal measurement invariance in four common rating scales of depression. Psychological Assessment, 28, 1354–1367. [Data & R-script]

Haslbeck, J., & Fried, E. I. (2016). How Predictable are Symptoms in Psychopathological Networks? A Reanalysis of 18 Published Datasets.

Isvoranu, A.-M., Borsboom, D., van Os, J., & Guloksuz, S. (2016). A Network Approach to Environmental Impact in Psychotic Disorder: Brief Theoretical Framework. Schizophrenia Bulletin, 42(4), 870–873.

Kossakowski, J. J., Epskamp, S., Kieffer, J. M., van Borkulo, C. D., Rhemtulla, M., & Borsboom, D. (2016). The application of a network approach to Health-Related Quality of Life (HRQoL): Introducing a new method for assessing HRQoL in healthy adults and cancer patients. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 25(4), 781–792.

Kruis, J., & Maris, G. (2016). Three representations of the Ising model. Scientific Reports, 6(1), Article 1.

Nuijten, M. B., Deserno, M. K., Cramer, A. O. J., & Borsboom, D. (2016). Mental disorders as complex networks: An introduction and overview of a network approach to psychopathology. Clinical Neuropsychiatry: Journal of Treatment Evaluation, 13, 68–76.

Olde Rikkert, M. G. M., Dakos, V., Buchman, T. G., Boer, R. de, Glass, L., Cramer, A. O. J., Levin, S., van Nes, E., Sugihara, G., Ferrari, M. D., Tolner, E. A., van de Leemput, I., Lagro, J., Melis, R., & Scheffer, M. (2016). Slowing Down of Recovery as Generic Risk Marker for Acute Severity Transitions in Chronic Diseases. Critical Care Medicine, 44(3), 601–606.

Rhemtulla, M., Fried, E. I., Aggen, S. H., Tuerlinckx, F., Kendler, K. S., & Borsboom, D. (2016). Network analysis of substance abuse and dependence symptoms. Drug and Alcohol Dependence, 161, 230–237. [R-script]

Tio, P., Epskamp, S., Noordhof, A., & Borsboom, D. (2016). Mapping the manuals of madness: Comparing the ICD-10 and DSM-IV-TR using a network approach. International Journal of Methods in Psychiatric Research, 25(4), 267–276.

van Borkulo, C. D., Borsboom, D., & Schoevers, R. A. (2016). Group-Level Symptom Networks in Depression—Reply. JAMA Psychiatry, 73(4), 411–412.

Wichers, M., & Groot, P. C. (2016). Critical Slowing Down as a Personalized Early Warning Signal for Depression. Psychotherapy and Psychosomatics, 85(2), 114–116. [Data]


Boschloo, L., van Borkulo, C. D., Rhemtulla, M., Keyes, K. M., Borsboom, D., & Schoevers, R. A. (2015). The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders. PLOS ONE, 10(9), e0137621.

Bringmann, L. F., Lemmens, L. H. J. M., Huibers, M. J. H., Borsboom, D., & Tuerlinckx, F. (2015). Revealing the dynamic network structure of the Beck Depression Inventory-II. Psychological Medicine, 45(4), 747–757.

Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. J. (2015). State of the aRt personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality, 54, 13–29. [Data & R-script in article]

Cramer, A. O. J., & Borsboom, D. (2015). Problems attract problems: A network perspective on mental disorders.

Epskamp, S. (2015). semPlot: Unified Visualizations of Structural Equation Models. Structural Equation Modeling: A Multidisciplinary Journal, 22(3), 474–483. [Data & R-script in article]

Fried, E. I. (2015). Problematic assumptions have slowed down depression research: Why symptoms, not syndromes are the way forward. Frontiers in Psychology, 6.

Fried, E. I., Bockting, C., Arjadi, R., Borsboom, D., Amshoff, M., Cramer, A. O. J., Epskamp, S., Tuerlinckx, F., Carr, D., & Stroebe, M. (2015). From loss to loneliness: The relationship between bereavement and depressive symptoms. Journal of Abnormal Psychology, 124, 256–265.

Fried, E. I., Boschloo, L., van Borkulo, C. D., Schoevers, R. A., Romeijn, J.-W., Wichers, M., de Jonge, P., Nesse, R. M., Tuerlinckx, F., & Borsboom, D. (2015). Commentary: “Consistent Superiority of Selective Serotonin Reuptake Inhibitors Over Placebo in Reducing Depressed Mood in Patients with Major Depression”. Frontiers in Psychiatry, 6.

Fried, E., Sluis, S., & Cramer, A. (2015). The genetics of major depression remain elusive.

Marsman, M., Maris, G., Bechger, T., & Glas, C. (2015). Bayesian inference for low-rank Ising networks. Scientific Reports, 5(1), Article 1.

McNally, R. J., Robinaugh, D. J., Wu, G. W. Y., Wang, L., Deserno, M. K., & Borsboom, D. (2015). Mental Disorders as Causal Systems: A Network Approach to Posttraumatic Stress Disorder. Clinical Psychological Science, 3(6), 836–849. [Data] [R-script] [Questionnaire]

Ruzzano, L., Borsboom, D., & Geurts, H. M. (2015). Repetitive behaviors in autism and obsessive-compulsive disorder: New perspectives from a network analysis. Journal of Autism and Developmental Disorders, 45(1), 192–202.

Schmittmann, V. D., Jahfari, S., Borsboom, D., Savi, A. O., & Waldorp, L. J. (2015). Making Large-Scale Networks from fMRI Data. PLOS ONE, 10(9), e0129074.

van Borkulo, C., Boschloo, L., Borsboom, D., Penninx, B. W. J. H., Waldorp, L. J., & Schoevers, R. A. (2015). Association of Symptom Network Structure With the Course of Depression. JAMA Psychiatry, 72(12), 1219–1226.

Waldorp, L. J., & Schmittmann, V. D. (2015). Computing Assortative Mixing by Degree with the s -Metric in Networks Using Linear Programming. Journal of Applied Mathematics, 2015(none), 1–9.

Wigman, J. T. W., van Os, J., Borsboom, D., Wardenaar, K. J., Epskamp, S., Klippel, A., MERGE, Viechtbauer, W., Myin-Germeys, I., & Wichers, M. (2015). Exploring the underlying structure of mental disorders: Cross-diagnostic differences and similarities from a network perspective using both a top-down and a bottom-up approach. Psychological Medicine, 45(11), 2375–2387.


van Borkulo, C. D., Borsboom, D., Epskamp, S., Blanken, T. F., Boschloo, L., Schoevers, R. A., & Waldorp, L. J. (2014). A new method for constructing networks from binary data. Scientific Reports, 4(1), Article 1.

van de Leemput, I. A., Wichers, M., Cramer, A. O. J., Borsboom, D., Tuerlinckx, F., Kuppens, P., van Nes, E. H., Viechtbauer, W., Giltay, E. J., Aggen, S. H., Derom, C., Jacobs, N., Kendler, K. S., van der Maas, H. L. J., Neale, M. C., Peeters, F., Thiery, E., Zachar, P., & Scheffer, M. (2014). Critical slowing down as early warning for the onset and termination of depression. Proceedings of the National Academy of Sciences, 111(1), 87–92. [Data & R-script in article]

Wichers, M., Borsboom, D., Tuerlinckx, F., Kuppens, P., Viechtbauer, W., van de Leemput, I. A., Kendler, K. S., & Scheffer, M. (2014). Reply to Bos and De Jonge: Between-subject data do provide first empirical support for critical slowing down in depression. Proceedings of the National Academy of Sciences, 111(10), E879–E879.


Borsboom, D., & Cramer, A. O. J. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91–121. [Data & R-script]

Bringmann, L. F., Vissers, N., Wichers, M., Geschwind, N., Kuppens, P., Peeters, F., Borsboom, D., & Tuerlinckx, F. (2013). A Network Approach to Psychopathology: New Insights into Clinical Longitudinal Data. PLOS ONE, 8(4), e60188. [Data] [R-script]

Schmittmann, V. D., Cramer, A. O. J., Waldorp, L. J., Epskamp, S., Kievit, R. A., & Borsboom, D. (2013). Deconstructing the construct: A network perspective on psychological phenomena. New Ideas in Psychology, 31(1), 43–53.


Cramer, A. O. J., Borsboom, D., Aggen, S. H., & Kendler, K. S. (2012). The pathoplasticity of dysphoric episodes: Differential impact of stressful life events on the pattern of depressive symptom inter-correlations. Psychological Medicine, 42(5), 957–965.

Cramer, A. O. J., van der Sluis, S., Noordhof, A., Wichers, M., Geschwind, N., Aggen, S. H., Kendler, K. S., & Borsboom, D. (2012). Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can’t Like Parties if You Don’t Like People. European Journal of Personality, 26(4), 414–431.

Cramer, A. O. J., Van Der Sluis, S., Noordhof, A., Wichers, M., Geschwind, N., Aggen, S. H., Kendler, K. S., & Borsboom, D. (2012). Measurable Like Temperature or Mereological like Flocking? On the Nature of Personality Traits. European Journal of Personality, 26(4), 451–459.

Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). qgraph: Network Visualizations of Relationships in Psychometric Data. Journal of Statistical Software, 48, 1–18. [Data & R-script in article]


Borsboom, D., Cramer, A. O. J., Schmittmann, V. D., Epskamp, S., & Waldorp, L. J. (2011). The Small World of Psychopathology. PLOS ONE, 6(11), e27407. [Data & R-script]

Borsboom, D., Epskamp, S., Kievit, R. A., Cramer, A. O. J., & Schmittmann, V. D. (2011). Transdiagnostic Networks: Commentary on Nolen-Hoeksema and Watkins (2011). Perspectives on Psychological Science, 6(6), 610–614.

Dutilh, G., Wagenmakers, E.-J., Visser, I., & van der Maas, H. L. J. (2011). A phase transition model for the speed-accuracy trade-off in response time experiments. Cognitive Science, 35(2), 211–250.


Cramer, A. O. J., Waldorp, L. J., van der Maas, H. L. J., & Borsboom, D. (2010). Comorbidity: A network perspective. The Behavioral and Brain Sciences, 33(2–3), 137–150; discussion 150-193.

Grasman, R., van der Maas, H. L., & Wagenmakers, E.-J. (2010). Fitting the cusp catastrophe in R: A cusp package primer. Journal of Statistical Software, 32, 1–27.

Schuurman, N. K. (2010). Exploratory time series modeling of individuals with burn-out. Unpublished internship report.

Before 2010

Borsboom, D. (2008). Psychometric perspectives on diagnostic systems. Journal of Clinical Psychology, 64(9), 1089–1108.

Hartelman, P. A., van der Maas, H. L. J., & Molenaar, P. C. M. (1998). Detecting and modelling developmental transitions. British Journal of Developmental Psychology, 16, 97–122.

van der Maas, H. L. J., Dolan, C. V., Grasman, R. P. P. P., Wicherts, J. M., Huizenga, H. M., & Raijmakers, M. E. J. (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review, 113(4), 842–861.

van der Maas, H. L. J., Kolstein, R., & van der Pligt, J. (2003). Sudden Transitions in Attitudes. Sociological Methods & Research, 32(2), 125–152.

Van der Maas, H. L., & Molenaar, P. C. (1992). Stagewise cognitive development: An application of catastrophe theory. Psychological Review, 99, 395–417.