This is an example of a power analysis for a simple mediation model with observed variables (no latent variables). This example is for Mplus. The r (using simsem) counterpart can be found here:
If you are unsure of what the population regression parameter estimates should be (that is the beta values), and prior work in the literature is not proving helpful, you might consider using Cohen’s (1988) effect size guidelines of 0.10 = small, 0.30 = medium, and 0.50 = large.
Starting at line 1, three variables x, m, and y are being created. The sample will be n = 200 with 100 replications.
In the model population command, the variances of x, m, and y are being fixed to 1 to represent normally distributed variables. The beta coefficient y on m is set to .20, y on x is .20 and m on x is .20.
The sample model starts at line 13. If you studying power of your model and not the effects of model misspecification then you would likely want to make the sample model the same as the population model. The model indirect command estimates the indirect effects. Tech9 in the output command provides you with the results of the power analysis.