Burnout construct consists of three sub-dimensions such as exhaustion, cynicism and Interpersonal strain at work. can I take mean scores of the sub-dimensions and take their average to make a composite score of burnout or treat them separately in structural equation modeling
Dear Razia,
Factor score is more recommended over summated score or average score because it represents all variable loadings in the factor. You can obtain the scores for burnout by using data imputation under Analyze menu in Amos.
Good luck.
Dear Razia,
I do not know the exact nature research question, however, to use all the information your data gather (use single items as indicators of your latent burnout-diemensions) and model all other aspects within this model instead of deriving compisite scores or means is maybe preferrable. Maybe different aspects of burn out out aren't that highly interrelated and are probably differntly associated with different other constructs you are interested in.
However, here is an discussion that is related to your question, that is maybe helpful:
https://www.linkedin.com/grp/post/2469932-252651674
Best Luck, Manuel
Thanks Sir Didik and Sir Manuel for you valuable feedback, what I understand is that instead of using a composite score, I should take the effect of sub- dimensions distinctively on the outcome variables
Yes, as starting point I would try to model everything (your three subcompinents of burnout of, each with a seperate measurement model and all your outcome variables) within one model. As mentioned in the discussion-link i posted, it is may helpful to change to composite scores if your model is to complex to fit it. However, it depends on your theoretical foundation of your model, the nature of the dimensionality of burn out and so on...I think that there are a lot of good papers using SEM approaches in burn-out research, maybe it is helpful how they dealt with comparable questions.
Best, Manuel
Thanks Sir Manuel for your valuable guidance, I'm more clear now, thanks again
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