Please let me illustrate my question with a concrete example of power analysis for the following model (some irrelevant parts have been omitted to save space):
library (WebPower)
model.2f <- '
F1 =~ a*x1 + start (.55)*x1 + start (.7)*x2 + start (.7)*x3
F2 =~ b*x4 + start (.6)*x4 + start (.6)*x5 + start (.5)*x6
F1 ~~ start (1)*F1
F2 ~~ start (1)*F2
F1 ~~ start (.3)*F2
x1 ~~ start(.6)*x1
…
'
power.2f <- wp.mc.sem.basic(model = model.2f, indirect = NULL, nobs = 100, nrep = 5000)
summary (power.2f)
In the outputs, the power analysis results (MSE, SD, Power, Coverage) for the indicator variables, x1 and x4, of the two respective factors in the model are not available, though I have set both factors’ variances as 1 and the loadings of x1 and x4 as freely estimated. By “not available” I mean their corresponding output rows are like:
True Estimate MSE SD Power Coverage
F1 =~ x1 (a) 0.550 0.550 0.000 0.000 NaN 0.000
…
F2 =~ x4 (b) 0.600 0.600 0.000 0.000 NaN 0.000
Grateful if you could advise how the power analysis results can be displayed for ALL the indicator variables (x1 – x6 in this case) of a measurement model when the latent variables they indicate have been set to have unit variances.
