References
- American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). American Psychiatric Association.
- Ashkin, J., & Teller, E. (1943). Statistics of two-dimensional lattices with four components. Physical Review, 64(5–6), 178–184. https://doi.org/10.1103/PhysRev.64.178
- Bak, M., Drukker, M., Hasmi, L., & van Os, J. (2016). An n = 1 clinical network analysis of symptoms and treatment in psychosis. PLoS One. 11(e0162811), 1–15.
- Barabási, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.
- Bodner, N., Bringmann, L., Tuerlinckx, F., de Jonge, P., & Ceulemans, E. (2022) ConNEcT: A novel network approach for investigating the co-occurrence of binarypsychopathological symptoms over time. Psychometrika., 87(1), 107–132. https://doi.org/10.1007/s11336-021-09765-2
- Borsboom, D. (2008). Psychometric perspectives on diagnostic systems. Journal of Clinical Psychology, 64(9), 1089–1108. https://doi.org/10.1002/jclp.20503
- Borsboom, D., & Cramer, A. O. J. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9(1), 91–121. https://doi.org/10.1146/annurev-clinpsy-050212-185608
- Bos, E., & Wanders, R. (2016). Group-level symptom networks in depression. JAMA Psychiatry, 73(4), 411. https://doi.org/10.1001/jamapsychiatry.2015.3103
- Bos, F. M., Snippe, E., Bruggeman, R., Wichers, M., & van der Krieke, L. (2022). Insights of patients and clinicians on the promise of the experience sampling method for psychiatric care. Psychiatric Services, 70(1), 983–991. https://doi.org/10.1176/appi.ps.201900050
- Bos, F. M., Snippe, E., de Vos, S., Hartmann, J. A., Simons, C. J. P., van der Krieke, L., de Jonge, P., & Wichers, M. (2017). Can we jump from cross-sectional to dynamic interpretations of networks? Implications for the network perspective in psychiatry. Psychotherapy and Psychosomatics, 86(3), 175–177. https://doi.org/10.1159/000453583
- Bringmann, L. F., & Eronen, M. I. (2018). Don’t blame the model: Reconsidering the network approach to psychopathology. Psychological Review, 125(4), 606–615. https://doi.org/10.1037/rev0000108
- Broadbent, S., & Hammersley, J. (1957). Percolation processes I. Crystals and mazes. Mathematical Proceedings of the Cambridge Philosophical Society, 53(3), 629–641. https://doi.org/10.1017/S0305004100032680
- Brusco, M., Steinley, D., Hoffman, M., Davis-Stober, C., & Wasserman, S. (2022). On Ising models and algorithms for the construction of symptom networks in psychopathological research. Psychological Methods, 24(6), 735–753. https://doi.org/10.1037/met0000207.
- Brush, S. G. (1967). History of the Lenz-Ising model. Reviews of Modern Physics, 39(4), 883–893. https://doi.org/10.1103/RevModPhys.39.883
- Cai, H. (2017). A note on jointly modeling edges and node attributesn of a network. Statistics and Probability Letters, 121, 54–60. https://doi.org/10.1016/j.spl.2016.10.014
- Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., Meier, M. H., Ramrakha, S., Shalev, I., Poulton, R., & Moffitt, T. E. (2014). The p factor: One general psychopathology factor in the structure of psychiatric disorders? Clinical Psychological Science: A Journal of the Association for Psychological Science, 2(2), 119–137. https://doi.org/10.1177/2167702613497473
- Cioletti, L., & Vila, R. (2016). Graphical representations for Ising and Potts models in general external fields. Journal of Statistical Physics, 162(1), 81–122. https://doi.org/10.1007/s10955-015-1396-5
- Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. (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. https://doi.org/10.1016/j.jrp.2014.07.003
- 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. https://doi.org/10.1016/j.paid.2017.06.011
- Cox, D. (1972). The analysis of multivariate binary data. Journal of the Royal Statistical Society. Series B (Applied Statistics), 21(2), 113–120. https://doi.org/10.2307/2346482
- 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), e0167490–20. https://doi.org/10.1371/journal.pone.0167490
- 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. https://doi.org/10.1002/per.1866
- 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), 137–193. https://doi.org/10.1017/S0140525X09991567
- Csardi, G., Nepusz, T. (2019). igraph: Network analysis and visualization [Computer software manual]. Retrieved from https://CRAN.R-project.org/package=igraph (R-package version 1.2.4.2.)
- Dalege, J., Borsboom, D., van Harreveld, F., van den Berg, H., Conner, M., & van der Maas, H. L. J. (2016). Towards a formalized acount of attitudes: The causal attitude network (CAN) model. Psychological Review, 123(1), 2–22. https://doi.org/10.1037/a0039802
- 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. https://doi.org/10.1177/1948550617709827
- Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. J. (2019). A network perspective on political attitudes: Testing the connectivity hypothesis. Social Psychological and Personality Science, 10(6), 746–756. https://doi.org/10.1177/1948550618781062
- De Vos, S., Wardenaar, K. J., Bos, E. H., Wit, E. C., Bouwmans, M. E. J., & de Jonge, P. (2017). An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks. PloS One, 12(6), e0178586–18.
- 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(4), 1–18. Retrieved from http://www.jstatsoft.org/v48/i04/ https://doi.org/10.18637/jss.v048.i04
- Epskamp, S., Fried, E. I., van Borkulo, C. D. Robinaugh, D. J., Marsman, M., & Dalege, J. (2022) Investigating the utility of fixed-margin sampling in network psychometrics. Multivariate Behavioral Research, 56(2), 314–328. https://doi.org/10.1080/00273171.2018.1489771
- Epskamp, S., Maris, G., Waldorp, L., & Borsboom, D. (2018). Network psychometrics. In P. Irwing, D. Hughes, & T. Booth (Eds.), Handbook of psychometrics (pp. 953–986). Wiley-Blackwell.
- Erdős, P., & Rényi, A. (1960). On the evolution of random graphs. Publications of the Mathematical Institute of the Hungarian Academy of Sciences, 5(1), 17–60.
- Fisher, A. J. (2015). Toward a dynamic model of psychological assessment: Implications for personalized care. Journal of Consulting and Clinical Psychology, 83(4), 825–836. https://doi.org/10.1037/ccp0000026
- Fisher, A. J., Medaglia, J. D., & Jeronimus, B. F. (2018). Lack of group-to-individual generalizability is a threat to human subjects research. Proceedings of the National Academy of Sciences, 115(27), E6106–E6115. https://doi.org/10.1073/pnas.1711978115
- Fisher, A. J., Reeves, J. W., Glenn, L., Medaglia, J. D., & Rubel, J. A. (2017). Exploring the idiographic dynamics of mood and anxiety via network analysis. Journal of Abnormal Psychology, 126(8), 1044–1056.
- Forbes, M. K., Wright, A. G. C., Markon, K. E., & Krueger, R. F. (2017). Evidence that psychopathology symptom networks have limited replicability. Journal of Abnormal Psychology, 126(7), 969–988. https://doi.org/10.1037/abn0000276
- Forbes, M. K., Wright, A. G. C., Markon, K. E., & Krueger, R. F. (2019). The network approach to psychopathology: Promise versus reality. World Psychiatry, 18(3), 272–273. https://doi.org/10.1002/wps.20659
- Forbes, M. K., Wright, A. G. C., Markon, K. E., & Krueger, R. F. (2022). Quantifying the reliability and replicability of psychopathology network characteristics. Multivariate Behavioral Research, 56(2), 224–242. https://doi.org/10.1080/00273171.2019.1616526.
- Fortuin, C. (1972a). On the random-cluster model: III. The simple random-cluster model. Physica, 59(4), 545–570. https://doi.org/10.1016/0031-8914(72)90087-0
- Fortuin, C. (1972b). On the random-cluster model II. The percolation model. Physica, 58(3), 393–418. https://doi.org/10.1016/0031-8914(72)90161-9
- Fortuin, C., & Kasteleyn, P. (1972). On the random-cluster model: I. Introduction and relation to other models. Physica, 57(4), 536–564. https://doi.org/10.1016/0031-8914(72)90045-6
- Fortuin, C., Kasteleyn, P., & Ginibre, J. (1971). Correlation inequalities on some partially ordered sets. Communications in Mathematical Physics, 22(2), 89–103. https://doi.org/10.1007/BF01651330
- 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.
- Geman, S., & Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6), 721–741.
- Grimmet, G. (2006). The random-cluster model. Springer-Verlag.
- Grimmett, G. (2018). Probability on graphs. Random processes on graphs and lattices (2nd ed.). Cambridge University Press.
- Häggström, O. (2001). Coloring percolation clusters at random. Stochastic Processes and Their Applications, 96(2), 213–242. https://doi.org/10.1016/S0304-4149(01)00115-6
- Häggström, O. (2002). Finite Markov chains and algorithmic applications. Cambridge University Press.
- Häggström, O., & Jonasson, J. (1999). Phase transition in the random triangle model. Journal of Applied Probability, 36(4), 1101–1115. Retrieved from https://www.jstor.org/stable/3215581 https://doi.org/10.1239/jap/1032374758
- Haslbeck, J., Epskamp, E., Marsman, M., & Waldorp, L. J. (2022). Interpreting the Ising model: The input matters. Multivariate Behavioral Research, 56(2), 303–313. https://doi.org/10.1080/00273171.2020.1730150
- Holland, P. W., Laskey, K. B., & Leinhardt, S. (1983). Stochastic blockmodels: First steps. Social Networks, 5(2), 109–137. https://doi.org/10.1016/0378-8733(83)90021-7
- Holland, P. W., & Rosenbaum, P. R. (1986). Conditional association and unidimensionality in monotone latent variable models. The Annals of Statistics, 14(4), 1523–1543. Retrieved from https://www.jstor.org/stable/2241486 https://doi.org/10.1214/aos/1176350174
- Ising, E. (1925). Beitrag zur theorie des ferromagnetismus. Zeitschrift Für Physik, 31(1), 253–258. https://doi.org/10.1007/BF02980577
- Jonasson, J. (1999). The random triangle model. Journal of Applied Probability, 36(3), 852–867. Retrieved from https://www.jstor.org/stable/3215446 https://doi.org/10.1239/jap/1032374639
- Karrer, B., & Newman, M. (2011). Stochastic blockmodels and community structure in networks. Physical Review E, 83(1), 016107. https://doi.org/10.1103/PhysRevE.83.016107
- Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J., & Borsboom, D. (2013). Simpson’s paradox in psychological science: A practical guide. Frontiers in Psychology, 4(513), 513–514.
- Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613.
- Langer, J. K., Tonge, N. A., Piccirillo, M., Rodebaugh, T. L., Thompson, R. J., & Gotlib, I. H. (2019). Symptoms of social anxiety disorder and major depressive disorder: A network perspective. Journal of Affective Disorders, 243, 531–538. https://doi.org/10.1016/j.jad.2018.09.078
- Lenz, W. (1920). Beiträge zum verständnis der magnetischen eigenschaften in festen körpern. Physikalische Zeitschrift, 21, 613–615.
- Maris, G., Bechger, T., & San Martin, E. (2015). A Gibbs sampler for the (extended) marginal Rasch model. Psychometrika, 80(4), 859–879.
- 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. https://doi.org/10.1080/00273171.2017.1379379
- Marsman, M., Maris, G. K. J., Bechger, T. M., & Glas, C. A. W. (2015). Bayesian inference for low-rank Ising networks. Scientific Reports, 5, 9050. https://doi.org/10.1038/srep09050
- Marsman, M., Maris, G. K. J., Bechger, T. M., & Glas, C. A. W. (2016). What can we learn from plausible values? Psychometrika, 81(2), 274–289.
- Marsman, M., Tanis, C. C., Bechger, T. M., & Waldorp, L. J. (2019). Network psychometrics in educational practice. Maximum likelihood estimation of the Curie-Weiss model. In B. P. Veldkamp & C. Sluijter (Eds.), Theoretical and practical advances in computer-based educational measurement (pp. 93–120). Springer.
- Marsman, M., Waldorp, L. J., & Borsboom, D. (2022). Towards an encompassing theory of network models: Reply to Brusco, Steinley, Hoffman, Davis-Stober, & Wasserman. Psychological Methods, (PsyArXiv: n98qt). https://doi.org/10.1037/met0000373
- McElroy, E., Fearon, P., Belsky, J., Fonagy, P., & Patalay, P. (2018) Networks of depression and anxiety symptoms across development. Journal of the American Academy of Child and Adolescent Psychiatry, 57(12), 964–973. https://doi.org/10.1016/j.jaac.2018.05.027
- Mislevy, R. J. (1991). Randomization-based inference about latent variables from complex samples. Psychometrika, 56(2), 177–196. https://doi.org/10.1007/BF02294457
- Newman, C. (1991). Disordered Ising systems and random cluster representations. In G. Grimmett (Ed.), Probability and phase transition (Vol. 420, pp. 247–260). Springer.
- Newman, M. (2012). Communities, modules and large-scale structure in networks. Nature Physics, 8(1), 25–31. https://doi.org/10.1038/nphys2162
- Niss, M. (2005). History of the Lenz-Ising model 1920–1950: From ferromagnetic to cooperative phenomena. Archive for History of Exact Sciences, 59(3), 267–318. https://doi.org/10.1007/s00407-004-0088-3
- Polson, N. G., Scott, J. G., & Windle, J. (2013). Bayesian inference for logistic models using Pólya-Gamma latent variables. Journal of the American Statistical Association, 108(504), 1339–1349. https://doi.org/10.1080/01621459.2013.829001
- Potts, R. B. (1952). Some generalized order-disorder transformations. Mathematical Proceedings of the Cambridge Philosophical Society, 48(1), 106–109. https://doi.org/10.1017/S0305004100027419
- R Core Team. (2019). R: A language and environment for statistical computing [Computer software manual]. Vienna, Austria. Retrieved from https://www.R-project.org/
- Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15(3), 351–357. https://doi.org/10.2307/2087176
- Saitz, R., Cheng, D. M., Winter, M., Kim, T. W., Meli, S. M., Allensworth-Davies, D., Lloyd-Travaglini, C. A., & Samet, J. H. (2013). Chronic care management for dependence on alcohol and other drugs: The AHEAD randomized trial. JAMA, 310(11), 1156–1167. https://doi.org/10.1001/jama.2013.277609
- 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.
- Savi, A. O., Marsman, M., van der Maas, H. L. J., & Maris, G. K. J. (2019). The wiring of intelligence. Perspectives on Psychological Science, 16(6), 1034–1061.
- Simpson, E. H. (1951). The interpretation of interaction in contingency tables. Journal of the Royal Statistical Society. Series B (Methodological), 13(2), 238–241. https://doi.org/10.1111/j.2517-6161.1951.tb00088.x
- Spearman, C. (1904). “General intelligence,” objectively determined and measured. The American Journal of Psychology, 15(2), 201–292. https://doi.org/10.2307/1412107
- Steif, J. E., Tykesson, J. (2017). Generalized divide and color models. Retrieved from https://arxiv.org/abs/1702.04296. (ArXiv preprint.)
- Steinley, D., Hoffman, M., Brusco, M. J., & Sher, K. J. (2017). A method for making inferences in network analysis: Comment on Forbes, Wright, Markon, and Krueger (2017). Journal of Abnormal Psychology, 126(7), 1000–1010. https://doi.org/10.1037/abn0000308
- Swendsen, R., & Wang, J. (1987). Nonuniversal critical dynamics in monte carlo simulations. Physical Review Letters, 58(2), 86–88.
- 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, 5918. https://doi.org/10.1038/srep05918
- van Borkulo, C., Wichers, M., Boschloo, L., Epskamp, S., Schoevers, R., & Kamphuis, J. (2017). The contact process as a model for predicting network dynamics of psychopathology.
- 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., Kan, K.-J., Marsman, M., & Stevenson, C. E. (2017). Network models for cognitive development and intelligence. Journal of Intelligence, 5(2), 16–17. https://doi.org/10.3390/jintelligence5020016
- Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440–442.