Anonymous posted on Sunday, June 20, 2004 - 11:08 am
I have a model with two continuous latent variables F1 and F2, and one categorical variable X (a binary 0/1 variable). I am interested by the standardized indirect effect from F1 to X. The statements of model are: F2 ON F1; X ON F2; X VIA F2 F1; Is it correct to consider the STDYX coefficient of the indirect effect as standardized probit regression coefficient ?
The standard errors given in the output are for the raw coefficients. They are not the standard errors for the standardized coefficients. You would need to compute these standard errors using the Delta method.
Anonymous posted on Tuesday, October 05, 2004 - 12:02 pm
Do you mean in Analysis command using Parameterization=delta; ?
This is the default paramerization of Mplus. The results are the same with or without using Parameterization=delta. if Type=general.
I do not know anything else about Delta method. Could you tell me the syntax needed for calculating S.E. or p-value of StdYX results?
No, it is not PARAMETERIZATION = DELTA. You will need to read about the Delta method for computing standard errors in a book like Bollen's SEM book.
Anonymous posted on Tuesday, October 05, 2004 - 12:34 pm
Daniel posted on Wednesday, March 30, 2005 - 10:34 am
I used bootstrap standard errors to assess the significance of an indirect effect on an ordered categorical dependent variable. The indirecte effect was signficant. Is it possible to compute an odds ratio (exponentiating the log odds Beta) and confidence interval using the indirect effect, or does that not make sense?
BMuthen posted on Saturday, April 02, 2005 - 8:27 pm
I think that makes sense if you are using maximum likelihood estimation which uses the logit model. The indirect effect still refers to a slope.
First, the output for 'model indirect' in Mplus lists the estimates, standard errors, and two-tailed p-values for each direct and indirect effect. My question is: What are the listed p-values testing? Are these p-values an indication of whether the indirect effects are significant?
Second, my model includes multiple mediators regressed upon each other. For example, one of the indirect paths is SES-->Social support-->Negative affect-->Self-efficacy-->Smoking relapse (categorical/binary). Is there a test to determine if this complex mediational/indirect path is significant? Is that what is already reported in the indirect output?
The test is whether the indirect effect is different from zero. The p-value is the value for the z-test given in column three, the ratio of the indirect effect to its standard error.
If you define the indirect effect as described above, it will be tested against zero. This is what is reported in the output.
Michael B posted on Tuesday, July 28, 2009 - 6:20 am
A reviewer requested that I describe how the indirect effects were tested. Can you refer me to a paper that describes what Mplus does to test this type of complex indirect effect? Is there a name for this type of test?
The standard errors for the indirect effects are estimated using the Delta method. The ratio of the parameter estimate to its standard error is a z-test.
Jo Brown posted on Wednesday, July 04, 2012 - 8:30 am
In the post above you mention that the SEs of the indirect effects are estimated using the Delta method. Is this robust to potential bias or should I still use bootstrapping to estimate bias-corrected SEs?