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You should put all your predictors into the model simultaneously, and they should predict every factor. Yes, this is MIMIC (multiple indicator, multiple cause) model. It's a MIMIC because each factor has indicators - that is, measure variables which it points to, and multiple causes - that is, measured variables that point to it. I don't know a paper off ...


Welcome to CV, Sunita. Generally speaking, yes, this would be an ill-advised approach. You can think of EFA as a data-driven theory-building approach, and CFA as a researcher-decision-driven theory-testing approach. In essence, running both analyses on the same sample of data would be akin to asking "What do the data tell me the latent structure looks like....


Mulaik, S. A. (2009). Linear Causal Modeling with Structural Equations. Chapman and Hall/CRC. This seems to be a mathematically thorough treatment of the subject.


They both may suggest a single factor but the CFA stats you are reporting reflect fit ... Some of those 8 items may not be reflective of the underlying factors as you intended ... Check the loadings and perhaps drop the appropriate items to watch the CFI go up and rmsea go down. Return here to let everyone know how you got on @drpaulburke

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