Philippe Rast works in the development, evaluation, and application of quantitative methods, mainly longitudinal models for examining change over time and how individuals differ in this change. He integrates mostly Bayesian methods for simultaneously examining intra-individual variability (change at the individual level) and inter-individual differences in such changes in the context of the examination of cognitive processes and changes in emotion and stress.
Philippe Rast's research interests are in individual differences in learning and cognitive development; improvement of prediction of cognitive decline using individual differences in learning functions; and the investigation of potential for improving, maintaining, and preventing decline of functioning across the adult lifespan. He has made contributions to the analysis and design of longitudinal studies, with particular emphasis on methods to disentangle within- and between-person change and variation in longitudinal designs.
His research also includes the development of single case models that allow one to estimate and predict behavior and behavioral consistency for single individuals. He is the author and co-author of multiple R-packages that are geared toward the modeling of within-person variability in high-frequency time series data.