

Power analysis for CFA of large scale 

Message/Author 


Hi all (first time posting here!), 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? Thanks! 


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. 

Back to top 

