Key points are not available for this paper at this time.
This article provides an application of structural equation modeling to the evaluation of cross-lagged panel models. Self-reports of physical and mental health at 3 different time points spanning a 4-year interval were analyzed to illustrate the cross-lagged analysis methodology. Data were collected from a sample of 856 patients with hypertension, diabetes, heart disease, or depression (or any combination of these) participating in the Medical Outcomes Study. Cross-lagged analyses of physical and mental health constructs revealed substantial stability effects across time. A structural model with standard effects revealed positive effects of physical health on mental health but negative (suppression) effects of mental health on physical health. The effects of mental health on physical health became nonsignificant when the model was revised by adding nonstandard effects (direct effects of measured variable residuals on latent variables). Recommendations for structural equation modeling of cross-lagged panel data are provided.
Hays et al. (1994) studied this question.