ABSTRACT
This chapter contains a methodology of aggregated time-series panel analysis (TSPA), by which prototypical process patterns can be modeled using longitudinal monitoring of psychotherapy process. TSPA will be contrasted with growth curve models of the same data set. The chapter shows that TSPA can illuminate change mechanisms of psychotherapy by exploiting recurrent temporal patterns in process data. A primary goal of the present empirical study was to model this samples therapy process using TSPA. The input data to TSPA comprised the entire body of process monitoring yielded by repeated application of the pre-session reports in 202 patients. Especially TSPA is a promising tool for psychotherapy process research because it is capable of providing answers to a core concern, the question of change mechanisms and causal relationships. The purpose of the chapter was to address methods for modeling psychotherapeutic change on the basis of repetitive measurements with a focus on time-series panel analysis (TSPA).
