Good day,
Currently, I analysed my collected data using PLS-SEM approach. Do I need to add explanatory or even confirmatory factor analysis to my analysis results?
Many thanks in advance
Confirmatory factor analysis (cfa) only for the factor based method as CBSEM that exemplified in certain statistical packages (amos, lisrel, mplus and many more). For the composite method as pls-sem, the confirmatory composite analysis (cca) should be used when assessing the measurement model
Dear Salah,
it depends what kind of estimator you used in the context of PLS-PM. PLSc is a consistent estimator for common factor models (the same model assumed in CFA), while PLS-PM (mode B) is a conistent estimator for composite models. So I would say they the CFA/EFA and PLS are not really comparable as the underlying model is different, similar like EFA vs. PCA.
And of course, it depends on your type of research, i.e., confirmatory vs predictive research. If your main goal is out-of-sample prediction, you might accept the bias of PLS-PM for common factor models. If your goal is confirmation (causal research) you should choose a consistent estimator.
Best regards,
Florian
The main purpose of conducting Exploratory Factor Analysis is to assess the validity and to reduce the number of measured items for the independent and dependent construct of the conceptual model. In the context of PLS-SEM, you have two ways to evaluate your suggested research model, 1. Assessment of measurement Model and 2. Assessment of structural Model. Exclusively, Assessment Measurement Model helps you to make sure the validity and reliability of the model. In this test, you may assess reliability through internal consistency reliability (Cronbach's alpha) and indicator reliability (Composite reliability ). However, validity would be measure through convergent validity and decrement validity.
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