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| crystal posted on Sunday, December 07, 2014 - 12:45 pm
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Hi I am trying to create a SEM model with a quadratic effect between my mediating variable and my outcome variable
(X1, X2 AND X3) all predict mediating variable and the mediating variable predicts Y1
X1------
X2----- mediating variable ------ Y1
X3-----
i want to model a quadratic relationship between mediating variable and y1. do i just add a power term of mediating variable (squared) and have it predict Y1? Also, do i need my exogenous variables predicting the squared term? |
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Create m2 in Define:
Define:
m2 = (m-mbar)*(m-mbar); !mbar = mean
Then use
Model:
y on m m2;
m on x1-x3;
Here, m2 will be a covariate and automatically correlated with x1-x3.
Because of the non-linearity I would ignore the chi-square testing. |
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Also, the indirect effect estimation is not straightforward in this case. Perhaps it could be derived from my paper on our website:
Muthén, B. (2011). Applications of causally defined direct and indirect effects in mediation analysis using SEM in Mplus. |
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Dear Mplus team,
I got huge lessons from your suggestion on the issue of handing the meditation model with a quadratic factor in the section "nonlinear factor analysis"
The model depiction follows (variables are latent and continuous except for outcome which is continuous but observed).
Y on X, X-squared, M
Y IND X;
Y IND X M;
The syntax with not this one. This describes what the model looks like.
However, I thought that the meaning of the coefficient of (X) in the model which quadratic term included is different from a model without the quadratic term (Tradition linear mediation model), due to the fact that the coefficient (c1b1+c2) represents the slope at X=0 rather than the slope of whole data.
A brief description of the quations of my model
M = b0 + b1(X) -- (1)
Y = c0 + c1(M) + c2(X) + c3 (X-squared) -- (2)
Y = c0 + b0c1 + (c1b1+c2)(X) + c3(X-squared) -- (3)
Hence, I am asking that if I can't express a linearly indirect effect and curvilinear relationships between X and Y at the same time. I found out a paper discussing a quadratic indirect effect but not in the case of my mine.
Thank you to respond to my question. |
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I don't understand how you can have both equations (2) and (3) in the same model. The model of (1) and (2) is expressed as
m on x;
y on m x x2;
where x2 is defined as x squared using XWITH. |
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