Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16, 5–13.
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, 1-13. 
Cramer, A. O. J., Waldorp, L. J., van der Maas, H., & Borsboom, D. (2010).Comorbidity: A network perspective. Behavioral and Brain Sciences, 33, 137-193.  
De Haan-Rietdijk, S., Gottman, J. M., Bergeman, C. S., & Hamaker, E. L. (2016). Get over it! A multilevel threshold autoregressive model for state-dependent affect regulation. psychometrika, 81(1), 217-241.
Driver, C. C., & Voelkle, M. C. (2018). Hierarchical Bayesian continuous time dynamic modeling. Psychological methods.
Driver, C. C., Oud, J. H., & Voelkle, M. C. (2017). Continuous time structural equation modeling with R package ctsem.
Ferrer, E., Steele, J. S., & Hsieh, F. (2012). Analyzing the dynamics of affective dyadic interactions using patterns of intra- and interindividual variability. Multivariate Behavioral Research, 47, 136–171.
Gates,  K.  M.,  &  Molenaar,  P.  C. (2012).Group  search  algorithm recovers effective connectivity maps for individuals in homogeneous and  heterogeneous  samples. NeuroImage, 63(1),  310  -  319.
Geschwind, N., Peeters, F., Drukker, M., van Os, J., & Wichers, M.  (2011). Mindfulness training increases momentary positive emotions and reward experience in adults vulnerable to depression:  a randomized controlled trial. Journal of Consulting and Clinical Psychology, 79,618–628
Hamaker, E. L. (2012). Why researchers should think “within-person”: A paradigmatic rationale. Handbook of research methods for studying daily life, 43-61.
Hamaker, E. L., Ceulemans, E., Grasman, R. P. P. P., & Tuerlinckx, F. (2015). Modeling affect dynamics: State of the art and future challenges. Emotion Review, 7(4), 316-322.
Hamaker, E. L., Grasman, R. P., & Kamphuis, J. H. (2010). Regime-switching models to study psychological process.
Hamaker, E. L., & Grasman, R. P. (2015). To center or not to center? Investigating inertia with a multilevel autoregressive model. Frontiers in psychology, 5, 1492.
Koval, P., Kuppens, P., Allen, N. B., & Sheeber, L. (2012). Getting stuck in depression: The roles of rumination and emotional inertia. Cognition & emotion, 26(8), 1412-1427.
Kuppens, P., Allen, N. B., & Sheeber, L. B. (2010). Emotional inertia and psychological maladjustment. Psychological Science, 21(7), 984-991.
Kuppens, P., Sheeber, L. B., Yap, M. B., Whittle, S., Simmons, J. G., & Allen, N. B. (2012). Emotional inertia prospectively predicts the onset of depressive disorder in adolescence. Emotion, 12(2), 283.
Oravecz, Z., & Tuerlinckx, F.  (2011).  The linear mixed model and the hierarchical ornstein–uhlenbeck model: Some equivalences and differences. British Journal of Mathematical and Statistical Psychology ,
64 (1), 134–160
Ou, L., Hunter, M. D., & Chow, S. (2017). What’s for dynr: A package for linear and nonlinear dynamic modeling in R. Journal of Statistical Software.
Schuurman, N.K., Ferrer, E., de Boer-Sonnenschein, M., & Hamaker, E.L. (2016). Studying individual differences in cross-lagged associations by standardizing multilevel autoregressive models. Psychological Methods.
Schuurman, N.K., Grasman, R.P.P.P., & Hamaker, E.L. (2016). A comparison of Inverse-Wishart prior specifications for covariance matrices in multilevel autoregressive models. Multivariate Behavioral Research.
Schuurman, N.K. & Hamaker, E.L. (2018). Measurement error and person-specific reliability in multilevel autoregressive models. Psychological Methods.
Schuurman, N.K., Houtveen, J.H., & Hamaker, E.L. (2015). Incorporating measurement error in n=1 psychological autoregressive modeling. Frontiers in Psychology, 6. doi: 10.3389/fpsyg.2015.01038
Sonnenschein, M., Sorbi, M., van Doornen, L., Schaufeli, W., & Maas, C. (2007). Electronic diary evidence on energy erosion in clinical burnout. Journal of Occupational Health Psychology, 12, 402–413.