Dear Mailinglist,

I might have to solve this problem in R. MPLUS support tell me they cannot
help me because the question is not MPLUS specific enough.

I am not sure where to inquire about this, maybe you guys can help me out.

I'm running something that is basically a mixed effects model in MPLUS,
which is set up as growth model. I allow every person to have its own
intercept and slope.

5 measurement points, 1 ordered dependent variable (0-3), quadratic growth
term has better fit, so I use a quadratic slope.

I am predicting intercept and slope by two covariates, one is a centered
metric (intelligence), the other nominal (gender).

Results:
Intercept: gender is significant (negative estimate -0.6)
Slope: gender is significant (positive estimate 0.2)

I want to plot this covariate now, over time (male vs female), and am not
sure how to do this.

(1) Coding is 1=female, 0=male. Do I understand correctly that this means
that males are higher at baseline (higher by 0.6 points on the dependent
variable, I guess?), and that females rise higher in the slope? Do they
rise by 0.2 per measurement point on the dependent variable, or 0.2 over
all 5 measurement points, or something entirely different?

(2) How can I find out whether the two trajectories meet (males start
higher, females rise quicker ...)? That is, do females overtake males at
some point, or are maler going to be higher throughout?

(3) If the effects were not on gender, but on a centered, metric variable,
like intelligence - what exactly would -0.6 and 0.2 mean?

Thank you
Eiko

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