The i BY statement defines the intercept growth factor. The s BY statement defines the slope growth factor. The statement [math7-math10@0]; fixes the intercepts of the outcomes at zero which is part of the growth model parametrization. The statement [i s]; frees the means of the intercept and slope growth factors.
JM posted on Wednesday, February 18, 2009 - 9:34 pm
Thanks for your previous post - very helpful. I have another question (sorry!). I'm running an LGM regressing the i and s on a covariate. When I regressed one of my covariates onto both the i and s, I got a significant positive effect on the intercept, and a significant, negative estimate (est: -0.127 est/S.E. -2.149) on the slope. Does this mean that the higher the score on my covariate, the higher the initial level, and then the faster the drop in growth overtime? Or is it the slower the the drop in growth overtime? It is the result on the slope I want to double check. Thank you thank you!!
The growth factors i and s are continuous variables. The regression coefficients in the regression of i and s on a covariate are linear regression coefficients. The interpretation is that for a one unit change in x, i and s change the amount of the regression coefficient. In one case the change is positive and in the other it is negative.