*This guest post was written by Sacha Epskamp (sacha.epskamp@gmail.com) who recently finished his PhD on Network Psychometrics at the University of Amsterdam. Sacha is well known for his various contributions to the development and application of network models, and for his numerous R-packages such as qgraph. *

As rain and students start pouring into the campus again, it is time to accept that summer is over and a new academic year is about to start. To me, the (academic) highlight of the summer definitely was the 2017 international meeting of the Psychometric Society (IMPS) in Zurich.

As always, IMPS was filled with plenty of state-of-the-art psychometrics. But this year, something was different. I reckon about half the Psychological Dynamics Facebook group showed up in Zurich to present about the latest work in analyses involving dynamical systems, time-series, networks and complexity. In addition to multiple keynotes and assorted talks in parallel sessions, there was an impressive number of five symposia related to the above topics. Over the summer, I have collected presentation slides of these great talks, which are listed below. Please let me know if you feel your slides should be added to this list.

#### Keynotes

Multiple relevant keynotes discussed both stochastic and social network analysis in detail. Besides the slides listed here, I found the presentation by Willem Heiser on the Gaussian graphical model and Han van der Maas on complexity in psychology very interesting.

- Bühlmann, P.: Heterogeneous Large-Scale Data: New Opportunities for Causal Inference and Prediction
- Snijders, S.: Network Analysis: Goodbye to Independence Assumptions

#### Networks and Latent Variable Models: Equivalences, Distinctions and Combinations

In my own symposium, we discussed the overlap and distinctions between latent variable models and network models. First, we discussed how these can be equivalent, next we discussed how these can be combined and finally we discussed how they can be separated.

- Kruis, J.: Three Representations of the Ising Model
- Epskamp, S: Generalized Network Psychometrics: Combining Network and Latent Variable Models
- Van Bork, R: How to Think of Model Complexity?
- Hofman, A: A Comparison of Latent Variable vs. Network Models Using Longitudinal Data

#### Intensive Longitudinal Data: Past, Present, and Future

The invited symposium on intensive longitudinal data discussed the state-of-the-art of dynamical modeling of time-series data.

- Hamaker, E.: A Brief History of Dynamic Modeling in Psychology
- Völkle, M.: Time Stops for No One: A Continuous Time Perspective on Dynamic Modeling

#### Recent Extensions to Autoregressive Models in Psychology

The second symposium on intensive longitudinal data discussed methodological advances in autoregressive modeling.

- Albers, C.: Modelling Smooth and Sudden Changes in Temporal Dynamics of (V)AR-Models
- Schuurman, N.: Measurement Error and Person-Specific Reliability in Multilevel Autoregressive Models

#### Networks in Psychology: Recent Developments

The THIRD symposium on intensive longitudinal data took a more high-dimensional approach and discussed advances in dynamic network modeling.

- Bringmann, L.: Inferring Changing Networks With Time Varying Vector Autoregressive Models
- Cabaço, T.: Time, Dynamics and Psychology Using the Gaussian Graphical Model
- Kossakowski, J.: Transforming Mutations into Models: Inferring Causal Networks from Experimental Data
- Tio, P.: Estimating Cross-Source Relationships From Big Data Using Component- and Networks-Analysis

#### IRT is Just Another Network Model

This symposium brought an unique group of researchers together in the same room: researchers that all have been working with the Ising model in psychometrics. The symposium lead to great discussions on the interpretation of statistical models in light of model equivalences.

- Marsman, M.: Relating Ising Network Models to Item Response Theory
- Anderson, C.: Network Multidimensional Item Response Models: Beyond Simple Structure
- Wermuth , N.: On the Symmetric Quadratic Exponential Distribution

#### Parallel sessions

Below are more presentations I found interesting but were not part of a single relevant symposium.