Rob White posted on Monday, April 26, 2010 - 4:44 pm
1. Is there a reference available that reports the Mplus method for calculating indirect effects from a SEM with intermediate outcomes that include binary, categorical, count and continuous measures?
2. How can I save the estimated indirect effects, total effects and their standard errors in an ascii file? I don't see them in the RESULTS ARE output (or the ESTIMATES ARE) and really do not want to have to calculate these myself.
1. There is no reference that I know of. 2. You do not need to calculate the indirect effects and their standard errors yourself, you can take them from the output.
Rob White posted on Wednesday, April 28, 2010 - 3:11 pm
1. Where can I read an explanation of how Mplus is calculating indirect effects from a SEM with intermediate outcomes that include binary, categorical, count and continuous measures?
2. I see that the indirect effects and their standard errors are in the .txt output. But I want to retrieve them from the ascii file that is generated by RESULTS ARE. They are not there. How can I save the indirect effects and their standard errors in an ascii file?
Hi Linda, I am interested in indirect effects in a mediation model across 5 waves. I am using an effects-coding method of scaling.
However, in the output the estimates are too small to see the values.
a) Is there an option to see more than 3 decimals for indirect effects?
b) I multiplied my data by a 100 hoping to resolve this problem, but it does not converge when I do this. Is there a reason that a simple rescaling to see more significant digits is having convergence problems?
In relations to your response to Craig's question re: calculations for the indirect effects, which is the product of two regression coefficients. I wonder how the system generates the significant level for the indirect effect. Take A --> B --> C, what if the A-->B path is nonsignificant? and what if these two paths (A-->B and B-->C) are significant at different levels.
As part of a mediation analysis I would like to report standardized indirect effects as unstandardized coefficients and SEs are extremely small. I am trying to figure out how best to use bootstrapping, if at all, to evaluate standardized indirect effects.
When using bootstrapping in conjunction with MODEL INDIRECT, is it appropriate to use the p-values for the standardized indirect effects using what I presume are bootstrapped SEs (the same way as with Delta method SEs and p-values) ?
Also, am I correct that examining whether Bias-corrected or standard bootstrapped CIs contain zero is not appropriate for standardized indirect effects?
Small unstandardized values may be due to x variables on a large scale. A simple solution is to use Define to scale down such variables by dividing by say 10.
You cannot use p-values for standardized to represent significance of unstandardized; they have different sampling distributions.
Ari J Elliot posted on Thursday, January 08, 2015 - 11:38 pm
Thank you very much for the reply and suggestion.
So would it be ok when reporting standardized indirect effects to use p-values in the output corresponding to the standardized coefficients, and is this appropriate when SEs are generated using bootstrapping?