Post conference: ‘Network modeling of timeseries data’
The post conference workshop on April 11 on ‘Network modeling of timeseries data: a theoretical introduction, a methodological primer, and some challenges‘ is taught by Angélique Cramer.
Recent years have witnessed a surge in fitting networks to timeseries (clinical) data that are often collected with the Experience Sampling Methodology (ESM). I will provide, firstly, an introduction to the network approach to psycho(patho)logy in which a psychological construct, e.g., major depression, is hypothesized to be the potential consequence of observable indicators (e.g., symptoms) that directly interact with one another in a network structure. Secondly, I will introduce one particular method, multilevel vector autoregressive (VAR) modeling with which one can estimate network structures both at group and at individual level. Finally, I will conclude by highlighting some challenges (e.g., inability of current network models to capture processes that operate at different timescales) that need to be met in order for the network approach to deliver on its promises.
Note that for this workshop we only have 20 places available and the room is located at the attic of the church with no elevator. Also, as there are no computers available in the conference center, all participants are requested to bring their own laptop to participate in the computer lab of the one-day workshops.