Response shift was identified over multiple occasions with a structural equation modeling framework

Abstract

Objective: To develop and apply a framework that uses structural equation modeling to identify response shift (RS) in data with more than two time points.

Study design and setting: The framework addresses key issues that arise when analyzing data with multiple time points using a model-based approach to test for RS: model validation, correction for multiple testing, and adoption of an exploratory or theory-driven approach to identify the type and timing of RS. Data from an observational study of 678 individuals at 1, 3, 6, and 12 months poststroke are used to demonstrate the application of the framework to a model for mental health.

Results: Uniform and nonuniform recalibration was identified at 6 and 12 months poststroke.

Conclusion: Studies that identify the type and timing of RS in certain client populations are useful for planning the timing of treatment and the methods to measure RS clinically. Validation of the model and adjusting for the effects of multiple testing increases confidence in the mental health model and the resulting identification of RS.