2019-09 Workshop - Network analysis workshop (FLAMES, Ghent)

Date created: | Last Updated:

: DOI | ARK

Creating DOI. Please wait...

Create DOI

Category: Communication

Description: The 2-day network workshop starts with a conceptual introduction on why items in psychological data tend to co-occur, and what this implies about the constructs we work with. This is followed by an introduction to social and psychological network models; an overview of the network literature in psychopathology (the field where network psychometric models have been used most over the last years); and a summary of important topics (centrality, comorbidity, early warning signals). The first group of statistical models we learn are network models in cross-sectional data. We will use the free statistical environment R to learn the basics about (1) network estimation, (2) network inference, and (3) network accuracy. We will finish this section with some advanced topics and methods, such as network comparisons, modeling of different types of variables, and considerations about causality. The statistical focus of day 2 is on dynamic time-series models: how do variables impact on each other over time? After an introduction into the general modeling framework, we learn to estimate network models for n=1 and n larger than 1 time-series data, followed by a discussion of some common problems and advanced techniques. We round up the workshop with a practical session where workshop participants learn to apply the knowledge to several datasets.

License: CC-By Attribution 4.0 International

Files

Loading files...

Citation

Tags

Recent Activity

Loading logs...

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.