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Future Blog Post

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Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

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Blog Post number 2

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Blog Post number 1

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Reproducibility Archives

I strive to make the code I use for analyses in all of my papers open and available through reproducibility archives, found through my publications page

Pancultural Nostalgia: Prototypical Conceptions Across Cultures

Published in Emotion, 2014

Recommended citation: Hepper, E. G., Wildschut, T., Sedikides, C., Ritchie, T. D., Yung, Y. F., Hansen, N.,...Ryan, O., & Stephan, E. & Vingerhoets, A. J. J. (2014). Pancultural Nostalgia: Prototypical Conceptions Across Cultures. Emotion, 14(4). https://psycnet.apa.org/doiLanding?doi=10.1037/a0036790

A systematic review of Bayesian articles in psychology: The last 25 years.

Published in Psychological Methods, 2017

Recommended citation: 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, 22(2), 217-239. https://psycnet.apa.org/doiLanding?doi=10.1037/met0000100

A continuous time approach to intensive longitudinal data: What, Why and How

Published in Continuous Time Modeling in the Behavioral and Related Sciences, 2018

Recommended citation: 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. https://link.springer.com/chapter/10.1007/978-3-319-77219-6_2

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

Published in Journal of Psychosomatic Research , 2018

Recommended citation: Bastiaansen, J.A., Kunkels, Y. K., ... Ryan, O., ... Albers, C.J., & Bringmann, L.F. https://www.sciencedirect.com/science/article/pii/S002239992030773X

Drawing conclusions from cross-lagged relationships: Re-considering the role of the time-interval

Published in Structural Equation Modeling, 2018

Recommended citation: 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. https://www.tandfonline.com/doi/abs/10.1080/10705511.2018.1431046

Meta-analysis of lagged regression models: A continuous-time approach

Published in Structural Equation Modeling, 2019

Recommended citation: Kuiper, R. M., & Ryan, O. (2020). Meta-analysis of lagged regression models: A continuous-time approach. Structural Equation Modeling: A Multidisciplinary Journal, 27(3), 396-413. https://www.tandfonline.com/doi/abs/10.1080/10705511.2019.1652613

A squared standard error is not a measure of individual differences

Published in Proceedings of the National Academy of Sciences , 2019

Recommended citation: Hamaker, E. L., & Ryan, O. (2019). A squared standard error is not a measure of individual differences. Proceedings of the National Academy of Sciences, 116(14), 6544-6545. https://www.pnas.org/content/116/14/6544.short

Choosing between AR (1) and VAR (1) models in typical psychological applications

Published in PloS One, 2020

Joint First Authorship

Recommended citation: 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. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240730

Comorbidity between depression and anxiety: assessing the role of bridge mental states in dynamic psychological networks

Published in BMC Medicine, 2020

Recommended citation: 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, 18(1), 1-17. https://link.springer.com/article/10.1186/s12916-020-01738-z

Dynamic Systems and Causal Structures in Psychology: Connecting Data and Theory

Published in , 2021

Doctoral Dissertation

Recommended citation: Ryan, O. (2020) Dynamic Systems and Causal Structures in Psychology: Connecting Data and Theory (Doctoral Dissertation). DOI: https://doi.org/10.33540/258. ISBN: 978-94-6416-145-8 https://doi.org/10.33540/258

Recovering within-person dynamics from psychological time series

Published in Multivariate Behavioral Research, 2021

Joint First Authorship

Recommended citation: Haslbeck, J. M.B * & Ryan, O.* (2021). Recovering within-person dynamics from psychological time series. Multivariate Behavioral Research, 1-32. https://www.tandfonline.com/doi/abs/10.1080/00273171.2021.1896353

Invisible hands and fine calipers: A call to use formal theory as a toolkit for theory construction

Published in Perspectives on Psychological Science, 2021

Recommended citation: 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. https://journals.sagepub.com/doi/abs/10.1177/1745691620974697

Modeling Psychopathology: From Data Models to Formal Theories

Published in Psychological Methods, 2021

Joint First Authorship with Haslbeck and Robinaugh

Recommended citation: 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. https://psycnet.apa.org/record/2022-00806-001

The Sum of All Fears: Comparing Networks Based on Symptom Sum-Scores

Published in Psychological Methods, 2021

Joint First Authorship

Recommended citation: Haslbeck, J.M.B*, Ryan, O.*, & Dablander, F.* (2021). The sum of all fears: Comparing networks based on symptom sum-scores. Psychological Methods. https://psycnet.apa.org/record/2022-14481-001

Modeling Change in Networks

Published in Network Psychometrics with R, 2022

Recommended citation: 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 (pp. 193-209). Routledge, New York https://link.springer.com/chapter/10.1007/978-3-319-77219-6_2

Time to intervene: A continuous-time approach to network analysis and centrality

Published in Psychometrika, 2022

Recommended citation: Ryan, O., & Hamaker, E. L. (2022). Time to intervene: A continuous-time approach to network analysis and centrality. Psychometrika, 87(1), 214–252 https://link.springer.com/article/10.1007/s11336-021-09767-0

(Pre-Print) Multimodality and Skewness in Emotion Time Series

Published in PsyArxiv, 2022

Joint First Authorship

Recommended citation: Haslbeck, J.M.B*, Ryan, O.*, & Dablander, F.* (2022, May 9). Multimodality and Skewness in Emotion Time Series. https://psyarxiv.com/qudr6

The Challenge of Generating Causal Hypotheses Using Network Models

Published in Structural Equation Modeling: A Multidisciplinary Journal, 2022

Recommended citation: Ryan, O., Bringmann, L. F., & Schuurman, N. K. (2022). The Challenge of Generating Causal Hypotheses Using Network Models. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705511.2022.2056039

(Pre-Print) Mapping the Timescale of Suicidal Thinking

Published in PsyArxiv, 2022

Pre-print here

Recommended citation: Coppersmith, D. D.L, Ryan, O., Fortgang, R.G., Millner, A.J, Kleiman, E.M, & Nock, M.K (2022) Mapping the Timescale of Suicidal Thinking. https://psyarxiv.com/eus2q

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Equilibrium Causal Models: Connecting Causal Models & Dynamical Systems

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Feedback loops and cyclic relationships are a mainstay of dynamical systems modelling, yet they are conspicuously absent in much of causal inference, where Directed Acyclic Graphs (DAGs) abound. Cycles do indeed have a place in causal inference, yet, in order to understand them, it is necessary to map causal models and causal intuitions back onto dynamical systems. To do this we can make use of Equilibrium Causal Models (ECMs), causal abstractions of dynamical systems which a) allow researchers to reason about the long time-scale effects of interventions and b) can potentially be learned from cross-sectional data. In this short talk, we give a brief motivation of ECMs, discuss how they relate to contemporary issues in psychological research, and sketch a simulation study to assess the feasibility of learning cyclic causal structures in practice.

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

Modeling Intensive Longitudinal Data in Discrete and Continuous Time: The basics

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As a pre-conference workshop to EAM 2021, myself and Noémi Schuurman gave a two part workshop on discrete and continuous-time modeling of time series data in R. The workshop materials can be found here

Modeling Intensive Longitudinal Data in Discrete-Time and Continuous-Time

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A two part workshop on discrete and continuous-time modeling of time series data in R. The workshop materials can be found here

Introduction to Causal Modeling (Parts 1 and 2)

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On November 7th and December 10th I gave a two part workshop to professional data scientists working at the University Medical Centre, Utrecht. The aim of the workshop was to introduce researchers to modern methods for causal modeling. Workshop materials for both days, including lecture slides and R lab materials, can be found here

Formal Theories in Psychology - What they are, why they matter, and how to build them

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This hands-on workshop introduced formal theories (computational models) to a general psychology audience, covering the motivation for computational modeling approaches, examples, getting started with formalization using causal graphs, and practical coding examples. The material of the workshop was prepared jointly with Don Robinaugh and Jonas Haslbeck. All workshop materials can be found here. The full workshop abstract can be found here