Hello!
In general, as a rule of thumb, what is the acceptable value for standardised factor loadings produced by a confirmatory factor analysis?
And, what could be done/interpretation if the obtained loadings are lower than the acceptable value?
How does everyone approach this?
I personally don't think that rules of thumb are helpful here because it really depends on what you can expect for your observed variables (factor indicators) under a given model. For example, for item-level data, we often would not expect very high reliabilities of individual items and, as a consequence, not very large standardized loadings. In contrast, for scale scores (composites, item parcels) that consist of many items, higher reliabilities and higher standardized loadings on the target factors would be expected.
Also, it depends on the model/type of factors. For example, in a bifactor or multitrait-multimethod (MTMM) model, high loadings on specific (or method) factors may not even be desirable.
@ Ravisha Jayawickrama. Most sources accept value for standardised factor loadings above 0.4
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