Abstract
State–space modeling techniques provide a convenient modeling platform for representing systematic trends as well as patterns of intraindividual variability around these trends. Their flexibility in accommodating multivariate processes renders them particularly suited to studying dyadic and family processes that show complex ebbs and flows over time. Using dyadic data collected during the Face-to-Face/Still-Face (FFSF) procedure, examples are provided to explicate the use of state–space models to capture two kinds of changes: systematic trends that are relatively smooth and slow-varying, and transient patterns of intraindividual variability that are manifested on a moment-to-moment basis.