A reviewer for a paper I wrote suggested that I conduct a power analysis in accordance with the MacCallum, Browne, and Sugawara paper for a CFA I did. The trouble is, the scale is pretty large. My understanding of SEM/CFA power analysis (based on my reading of MacCallum et al and a test using Preacher's online sem power calculator) is that with really high df I'll hit perfect power even with a tiny sample. My scale has almost df = 1000. Am I missing something, or would power analysis not be useful for my CFA?
I assume when you say your scale is large that you mean that you have many observed factor indicators and when you say your scale has df = 1000 this is the df for your H0 model. If I remember correctly the paper you refer to considers the overall power to reject the model if it is incorrect - you may ask yourself if is that what you are interested in. I can imagine that with a highly restricted model (with high df) you would have an easy time to reject the model due to small deviations. Or, are you interested in the power to reject that a certain parameter is zero? If I am not understanding you, please send the paper you refer to.