2019-06 Workshop - Network analysis in between-subjects data (VCU)

Contributors:

Date created: | Last Updated:

: DOI | ARK

Creating DOI. Please wait...

Create DOI

Category: Communication

Description: The workshop starts with a conceptual introduction on why items in psychological data tend to co-occur, and what this implies about the constructs such as mental disorders, cognitive abilities, personality, and attitudes. 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 main 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 and replicability. We will do so in both lectures and practicals. Please bring your laptops, make sure to have RStudio installed and running; a basic understanding of R is suggested. The last day of the workshop will cover advanced topics and methods, such as network comparisons, modeling of different types of variables, and considerations about causality. We will largely work with freely available data I provide, but if you have your own data you would like to investigate, feel free to bring it along. Note that consecutive sections in the workshop build on each other.

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.