Pre-prints

• Haqiqatkhah, M. M., Ryan, O., & Hamaker, E. L. Skewness and staging: Does the floor effect induce bias in multilevel AR(1) models? Pre-print
• Leertouwer, IJ., Vermunt, J. K., & Schuurman, N. K. Do People Gain Insight from Personalized Feedback about Distributions of their Affective Experiences? Pre-print
• Leertouwer, IJ., Vermunt, J. K., & Schuurman, N. K. A Pre-Post Design for Testing Insight from Personalized Feedback about Positive Affect in Contexts. Pre-print
• Robinaugh, D.J, Haslbeck, J. M. B., Waldorp, L., Kossakowski, J. J., Fried, E. I., Millner, A., McNally, R.J., Ryan, O., de Ron, J., van der Maas, H.L.J., van Nes, E.H., Scheffer, M., Kendler, K.S., & Borsboom, D.  Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder. Pre-print [R-package]
• Ryan, O.*, & Dablander, F.* Equilibrium Causal Models: Connecting Dynamical Systems Modeling and Cross-Sectional Data Analysis. Pre-print [reproducibility archive]
• Ryan, O.*, Dablander, F.* & Haslbeck, J. M. B.* Towards a Generative Model for Emotion Dynamics. Pre-print  [R-package] [reproducibility archive]
• Schuurman, N. K. A “Within/Between Problem” Primer: About (Not) Separating Within-Person Variance and Between-Person Variance in Psychology. Pre-print [app]

2023

• Berkhout, S. W., Schuurman, N. K., & Hamaker, E. L. (in press) A Tool to Simulate and Visualize Dyadic Interaction Dynamics. Psychological Methods.  [app]
• Coppersmith, D. D. L., Ryan, O., Fortgang, R. G., Millner, A. J., Kleiman, E. M., & Nock, M. K (in press). Mapping the Timescale of Suicidal Thinking. Proceedings of the National Academy of Sciences. Pre-print [reproducibility archive]
• Haslbeck, J. M. B*, Ryan, O.*, & Dablander, F.* (in press) Multimodality and Skewness in Emotion Time Series. Emotion. Pre-print [reproducibility Archive]

 2022

• Bringmann, L. F., Albers, C., Bockting, C., Borsboom, D., Ceulemans, E., Cramer, A., …, Hamaker, E. L., … & Wichers, M. (2022). Psychopathological networks: Theory, methods and practice. Behaviour Research and Therapy. Open Access
• Constantin, M. A., Schuurman, N. K., & Vermunt, J. K. (2022). General Monte Carlo Method for Sample Size Analysis in the Context of Network Models. Psychological Methods. Pre-print
• Cooke, E., Schuurman, N. K., & Zheng, Y. (2022). Examining the Within- and Between-Person Structure of a Short Form of the Positive and Negative Affect Schedule: A Multilevel and Dynamic Approach. Psychological Assessment.
• Hamaker, E. L. (2022). The Curious Case of the Cross-Sectional Correlation. Multivariate Behavioral Research. Open Access
• Haslbeck, J. M. B.*, & Ryan, O.*. (2022). Recovering within-person dynamics from psychological time series. Multivariate Behavioral Research. Open Access
• Haslbeck, J. M. B., Ryan, O., van der Maas, H. L., & Waldorp, L. J. Modeling Change in Networks. In A.M Isvoranu, S. Epskamp, L. J. Waldorp and D. Borsboom (eds.) Network Psychometrics with R. Routledge, New York. Open Access
• Leertouwer, IJ., Schuurman, N. K., & Vermunt, J. K. (2022). Are Retrospective Assessments Means of People’s Experiences? Journal for Person-Oriented Research. Open Access
• Mulder, J. D. (2022). Power Analysis for the Random Intercept Cross-Lagged Panel Model Using the powRICLPM R-Package. Structural Equation Modeling: A Multidisciplinary Journal. Open Access
• Ryan, O., Bringmann, L. F., & Schuurman, N. K. (2022). The challenge of generating causal hypotheses using network models. Structural Equation Modeling: A Multidisciplinary Journal. Open Access
• Ryan, O., & Hamaker, E. L. (2022). Time to intervene: A continuous-time approach to network analysis and centrality. Psychometrika. Open Access
• Spit, S., Andringa, S. & Ryan, O. (IPA). Investigating the relation between second language proficiency and study success using a causal inference approach.  In-Principle Accepted Pre-Registered Report. Language Learning. Pre-print

2021

• Alting van Geusau, V., Mulder, J. D., & Matthijssen, S. (2021). Predicting Outcome in an Intensive Outpatient PTSD Treatment Program Using Daily Measures. Journal of Clinical Medicine. Open Access
• Haslbeck, J. M. B.*, Ryan, O.*, & Dablander, F.* (2021). The sum of all fears: Comparing networks based on symptom sum-scores. Psychological Methods. Open Access
• Leertouwer, IJ., Cramer, A. O. J., Vermunt, J. K., & Schuurman, N. K. (2021). A Review of Explicit and Implicit Assumptions When Providing Personalized Feedback Based On EMA Data. Frontiers in Psychology. Open Access
• Hamaker, E. L., Asparouhov, T., & Muthén, B. (2021). Dynamic structural equation modeling as a combination of time series modeling, multilevel modeling, and structural equation modeling. The handbook of structural equation modeling. Open Access
• Haslbeck, J.M.B.* , Ryan, O.*, Robinaugh, D. J.* , Waldorp, L. J., & Borsboom, D. (2021). Modeling psychopathology: From data models to formal theories. Psychological Methods. Open Access
• Hofmans, J., Morin, A. J., Breitsohl, H., Ceulemans, E., Chénard-Poirier, L. A., Driver, C. C., …, Hamaker, E.L., … & Wille, B. (2021). The baby and the bathwater: On the need for substantive–methodological synergy in organizational research. Industrial and Organizational Psychology.
• Mulder, J. D., & Hamaker, E. L. (2021). Three Extensions of the Random Intercept Cross-Lagged Panel Model. Structural Equation Modeling: A Multidisciplinary Journal, 28(4), 638-648 . Open Access
• 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.
• Schuurman, T., Henrichs, L. F., Schuurman, N. K., Polderdijk, S., & Hornstra, L. (2021). Learning Loss in Vulnerable Student Populations after the COVID-19 school Closures. Scandinavian Journal of Educational Research. Open Access
• Schuurman, N. K., Zheng, Y. & Dolan, C.V. (2021). Multilevel dynamic twin modeling. Structural Equation Modeling: A Multidisciplinary Journal. Open Access; Supplemental Materials
• Zyphur, M. J., Hamaker, E. L., Tay, L., Voelkle, M., Preacher, K. J., Zhang, Z., … & Diener, E. F. (2021). From data to causes III: Bayesian priors for general cross-lagged panel models (GCLM). Frontiers in psychology. Open Access

2020

• Bastiaansen, J.A., Kunkels, Y. K., … Hamaker, E.L., …. Ryan, O., … Albers, C.J., & Bringmann, L.F. (2020) Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology. Journal of Psychosomatic Research. Open Access
• Dablander, F.*, Ryan, O.*, & Haslbeck, J. M. B* (2020). Choosing between AR (1) and VAR (1) models in typical psychological applications. PloS one. Open Access
• Groen, R. N., Ryan, O., Wigman, J. T., Riese, H., Penninx, B. W., Giltay, E. J., Wichers, M. & Hartman, C. A. (2020). Comorbidity between depression and anxiety: assessing the role of bridge mental states in dynamic psychological networks. BMC medicine. Open Access
• Hamaker, E. L., Mulder, J. D., & van IJzendoorn, M. H. (2020). Description, prediction and causation: Methodological challenges of studying child and adolescent development. Developmental cognitive neuroscience. Open Access
• Hamaker, E. L., & Muthén, B. (2020). The fixed versus random effects debate and how it relates to centering in multilevel modeling. Psychological methods.
• Kuiper, R. M., & Ryan, O. (2020). Meta-analysis of lagged regression models: A continuous-time approach. Structural Equation Modeling: A Multidisciplinary Journal. Open Access
• McNeish, D., & Hamaker, E. L. (2020). A primer on two-level dynamic structural equation models for intensive longitudinal data in Mplus. Psychological methods.
• Rikkert, M.G., Schuurman, N.K., & Melis, R. (2020). Complex systems, phase transitions and resilience in medicine and clinical psychology. In “Complex systems and population health.”
• Zyphur, M. J., Voelkle, M. C., Tay, L., Allison, P. D., Preacher, K. J., Zhang, Z., Hamaker, E.L., … & Diener, E. (2020). From data to causes II: Comparing approaches to panel data analysis. Organizational Research Methods. Open Access
• Zyphur, M. J., Allison, P. D., Tay, L., Voelkle, M. C., Preacher, K. J., Zhang, Z., Hamaker E.L, … & Diener, E. (2020). From data to causes I: Building a general cross-lagged panel model (GCLM). Organizational Research Methods. Open Access

2019

• Hamaker, E. L., & Ryan, O. (2019). A squared standard error is not a measure of individual differences. Proceedings of the National Academy of Sciences. Open Access
• Mulder, J. D., & Hamaker, E. L. (2021). Three extensions of the random intercept cross-lagged panel model. Structural Equation Modeling: A Multidisciplinary Journal, 28(4), 638-648. Open Access
• Schuurman, N.K. & Hamaker, E.L. (2019). Measurement error and person-specific reliability in multilevel autoregressive models. Psychological Methods.
• Usami, S., Murayama, K., & Hamaker, E. L. (2019). A unified framework of longitudinal models to examine reciprocal relations. Psychological methods.

2018

• Asparouhov, T., Hamaker, E. L., & Muthén, B. (2018). Dynamic structural equation models. Structural Equation Modeling: A Multidisciplinary Journal. Open Access
• Bringmann, L. F., Ferrer, E., Hamaker, E. L., Borsboom, D., & Tuerlinckx, F. (2018). Modeling non-stationary emotion dynamics in dyads using a time-varying vector-autoregressive model. Multivariate Behavioral Research. Open Access
• Hamaker, E. L., Asparouhov, T., Brose, A., Schmiedek, F. & Muthén, B. (2018). At the frontiers of modeling intensive longitudinal data: Dynamic structural equation models for the affective measurements from the COGITO study. Multivariate Behavioral Research.
• Kuiper, R. M., & Ryan, O. (2018). Drawing conclusions from cross-lagged relationships: Re-considering the role of the time-interval. Structural Equation Modeling: A Multidisciplinary Journal, 25(5), 809-823. Open Access
• Ryan, O., Kuiper, R. M., & Hamaker, E. L. (2018). A Continuous Time Approach to Intensive Longitudinal Data: What, Why and How? In In K. v. Montfort, J. H. L. Oud, & M. C. Voelkle (Eds.), Continuous Time Modeling in the Behavioral and Related Sciences. Springer, Cham. Open Access
• van de Schoot, R., Winter, S. D., Ryan, O., Zondervan-Zwijnenburg, M., & Depaoli, S. (2017). A systematic review of Bayesian articles in psychology: The last 25 years. Psychological Methods.

2017

• Asparouhov, T., Hamaker, E. L., & Muthén, B. (2017). Dynamic latent class analysis. Structural Equation Modeling: A Multidisciplinary Journal.
• 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.
• de Haan-Rietdijk, S., Voelkle, M. C., Keijsers, L., & Hamaker, E. L. (2017). Discrete- vs. continuous-time modeling of unequally spaced experience sampling method data. Frontiers in Psychology. Open Access
• Hamaker, E.L., Schuurman, N.K. & Zijlmans, Eva (2017). Using a few snapshots to distinguish mountains from waves: Weak factorial invariance in the context of trait-state research. Multivariate Behavioral Research.
• Hamaker, E. L., & Wichers, M. (2017). No time like the present: Discovering the hidden dynamics in intensive longitudinal data. (invited) Current Directions in Psychological Science.
• Van Emmerik, A. A. P., & Hamaker, E. L. (2017). Paint it black: Using change-point analysis to investigate the increasing vulnerability to depression towards the end of Vincent van Gogh’s life. Healthcare. Open Access

2016

• de Haan-Rietdijk, S., Kuppens, P., & Hamaker, E. L. (2016). What’s in a day? A guide to decomposing the variance in intensive longitudinal data. Frontiers in Psychology. Open Access
• Hamaker, E. L., Grasman, R. P. P. P., & Kamphuis, J. H. (2016). Modeling BAS dysregulation in Bipolar Disorder: Illustrating the potential of time series analysis (invited). Assessment (Special issue: Assessing Dynamic Psychological Processes).
• Schuurman, N.K. (2016). Multilevel Autoregressive Modeling in Psychology: Snags and Solutions. Doctoral dissertation (ISBN 978-90-393-6585-4). Utrecht University. Download pdf
• 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. (2016). Performance of the Normal VAR Model for Skewnormal and Truncated Normal Residuals Using AutovarCore (Technical Report). Groningen: Interdisciplinary Centre Psychopathology and Emotion regulation, Groningen University.

2015

• Bringmann, L. Ferrer, E., Hamaker, E. L., Borsboom, D., & Tuerlinckx, F. (2015). Modeling nonstationary emotion dynamics in dyads using a semiparametric time-varying vector autoregressive model. Multivariate Behavioral Research.
• 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 (Special issue: Affect Dynamics.
• Jongerling, J., Laurenceau, J.-P., & Hamaker, E. L. (2015). A multilevel AR(1) model: Allowing for inter-individual differences in trait-scores, inertia, and innovation variance. Multivariate Behavioral Research.
• Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. P. P. (2015). A critique of the cross-lagged panel model. Psychological Methods.
• Schuurman, N.K. (2015). Model Selection and Parameter Recovery Performance of AutovarCore Under Ideal Circumstances (Technical Report). Groningen: Interdisciplinary Centre Psychopathology and Emotion regulation, Groningen University.
• Schuurman, N.K., Houtveen, J.H., & Hamaker, E.L. (2015). Incorporating measurement error in n=1 psychological autoregressive modeling. Frontiers in Psychology. Open Access

2014

• Adolf, J., Schuurman, N. K., Borkenau, P., Borsboom, D., & Dolan, C. V. (2014). Measurement invariance within and between individuals: A distinct problem in testing the equivalence of intra- and inter-individual model structures. Frontiers in Psychology.
• De Haan-Rietdijk, S., Gottman, J. M., Bergeman, S., & Hamaker, E. L. (2014). Get over it! A multilevel threshold autoregressive model for state-dependent affect regulation. Psychometrika. Open Access
• Hamaker, E. L., & Grasman, R. P. P. P. (2014). To center or not to center? Investigating inertia with a multilevel autoregressive model. Frontiers in Psychology. Open Access

2012

• Hamaker, E. L. & Grasman, R. P. P. P. (2012). Regime switching state-space model applied to psychological processes: Handling missing data and making inferences. Psychometrika.
• Hamaker, E. L. (2012). Why researchers should think “within-person”: A paradigmatic rationale. Invited chapter for: M. R. Mehl & T. S. Conner (Eds.). Handbook of Research Methods for Studying Daily Life, 43-61, New York, NY: Guilford Publications.
• Wang, L., Hamaker, E. L. & Bergman, C. (2012). Investigating inter-individual differences in short-term intra-individual variability. Psychological Methods.

2011

• Jongerling, J. & Hamaker E. L. (2011). On the trajectories of the predetermined ALT model: What are we really modeling? Structural Equation Modeling.
• Madhyastha, T., Hamaker, E. L., & Gottman, J. (2011). Investigating spousal influence using moment-to-moment affect data from marital conflict. Journal of Family Psychology.

2010

• Houtveen, J. H., Hamaker, E. L., & Van Doornen, L. J. P. (2010). Using multilevel path analysis in analyzing 24-hour ambulatory physiological recordings applied to medically unexplained symptoms. Psychophysiology.
• Hamaker, E. L., Grasman, R. P. P. P., & Kamphuis, J. H. (2010). Regime-switching models to study psychological processes. In P. C. M. Molenaar & K. M. Newell (Eds.).Individual Pathways of Change: Statistical Models for Analyzing Learning and Development,155-168. Washington, DC: American Psychological Association.

(*) denotes joint-first authorship

Bold denotes membership of dynamic modelling lab at time of publication.