Message/Author |
|
gibbon lab posted on Wednesday, October 30, 2013 - 2:23 pm
|
|
|
Dear Professors I ran a mediation model like the following: x(continuous)->y(binary)->z(continuous). I used WLSMV estimation claiming that the binary mediator y is categorical. I wonder how I should interpret the coeficient, say beta2, for y(binary)->z(continuous). I understand that the model actually uses an underlying continuous variable y* in stead of y when estimating the path parameters. So if I am correct, the coefficient beta2 is the effect of y* on z (change in z when y* increases by 1 unit). But can I somehow convert this interpretation to the orginal scale of variable y? Like how much change in z when y changes from 0 to 1? Thanks a lot. |
|
|
Your understanding is correct. If you don't want y* to be the predictor, you should consider the causally-defined effects in my 2011 mediation paper which you find under Papers, Mediational Modeling. |
|
gibbon lab posted on Tuesday, November 05, 2013 - 10:53 am
|
|
|
Dear Professor, I actually like the results from the model I ran. The interpretation for total indirect path does not bother me since x and z are both manifest variables in the model. I am trying to find a way to interpret the coefficient beta2 for the second path y(binary)->z(continuous) so that people (e.g., paper reviewers) will unstandand it. I was just wondering if I can use E(z|y*>tau)-E(z|y*<tau) to estimate E(z|y=1)-E(z|y=0) where tau is the threshold estimated in Mplus to dichotomize y* into y. Thanks a lot. |
|
|
To me y > z is z ON y. If z is continuous, the coefficient is a linear regression coefficient. |
|
gibbon lab posted on Wednesday, November 06, 2013 - 8:14 am
|
|
|
Dear Linda, y* is the latent continuous variable (for y) in the path analysis: x(continuous)->y(binary)->z(continuous). I understand that the coefficient beta2 for the second path is a linear regression coefficient for y* (interpreted as the change in z when y* increases by 1 unit). What does that mean for the binary variable y? What is the difference in terms of z between the two groups indicated by y? Is it still beta2? That is where I am stuck. Thanks a lot. |
|
|
In the chain x -> y -> z where y is a binary variable, y is treated as y* using WLSMV and y using ML. See the following paper which is available on the website for further information: Muthén, B. (2011). Applications of causally defined direct and indirect effects in mediation analysis using SEM in Mplus. Submitted for publication. |
|
|
The expectation looks correct for WLSMV. |
|
gibbon lab posted on Thursday, November 07, 2013 - 10:13 am
|
|
|
Dear Linda, Thanks a lot. |
|
gibbon lab posted on Wednesday, November 13, 2013 - 8:00 am
|
|
|
Dear Professor, Is it true that the marginal distribution of y* is assumed to be the standard normal distribution N(0,1) in the model? Thanks. |
|
|
Y is a binary mediator, right? In which case normality is assumed for y* conditional on x. That is, it is the residual for y* that is assumed N(0,1). |
|
gibbon lab posted on Wednesday, November 13, 2013 - 12:13 pm
|
|
|
Dear Bengt, Yes, Y is binary. Thanks a lot for the clarification. |
|
Back to top |