Hi there. I have a question about comparing path estimates. Basically, I have 8 models with the same outcome variable across the 8 models, but different predictors in each model. There are 5 time points of data for both variables in each model. I have constrained the cross-lagged path from the predictor to the outcome variable to be the same at each time point, and so I essentially have one cross-lagged path estimate of interest from each model.

In summary, I have 8 cross-lagged path estimates from 8 different models for the same outcome variable….and I want to compare them. Could you explain how best to go about doing so? I’ve seen two approaches in the literature which don’t actually seem to be widely used: 1) The Cumming approach of testing for 50% overlap in the confidence intervals of the standardized regression coefficients, and 2) The Clogg et al. (1995) approach and calculate z scores from the standardized regression coefficients and their standard errors.

Would you recommend either of these? Thanks!

Also, for a more qualitative comparison between path estimates, surely the standardized regression coefficient is superior to the unstandardized??