Noémi’s research interests are idiographic modeling, dynamic modeling, multilevel modeling, Bayesian modeling, networks, scientific integrity, and philosophy of (psychological) science.

Her expertise is modeling intensive longitudinal data (DSEM), particularly with multilevel time series models. These models are used to model within-person processes as well as the differences across people in these processes. Her work on multilevel VAR models has been incorporated in the DSEM module of Mplus. Particularly, her work on standardizing multilevel (VAR) models has been incorporated as the standard for standardizing all Bayesian multilevel models in Mplus.  

Her current focus is on measurement issues and measurement modeling of intensive longitudinal data. For example, in a recent paper she considers the effects of disregarding measurement error, and how to estimate person-specific and item-specific reliability in the context of intensive longitudinal data.

For more information on her research you can visit Noémi’s personal website.