The final path model was initially tested with the background demographic variables predicting
the baseline latent variables.
In turn, all of
the baseline latent variables predicted the outcome latent variables.
We also report whether there were significant indirect effects on 18 - month outcomes of any demographic baseline predictors mediated through
the baseline latent variables.
Not exact matches
An alternative approach would be to model the variance shared by a set of proximal targets as a
latent variable, and employ the
latent variable to estimate both
baseline target levels and subsequent change in the targeted mechanism within a BTMM design.
Baseline target, posttest target, posttest outcome, and follow - up outcome are all measured as
latent variables.