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Is it Wright to do EFA and CFA on the same sample?
Once you have factors that fit your data, there is no point in running a CFA with the same sample. The only thing you would get is a really good model-fit, which is not surprising. You sample size is sufficient for both EFA and CFA.
What comes first EFA or CFA?
Definitely, you should run first the EFA and then run CFA according the structure obtained from EFA.
Can we do CFA without EFA?
Scholars suggest that adopted scales with sufficient empirical and theoretical evidence can be taken directly to CFA without running EFA beforehand (Hurley et al., 1997).
Is CFA better than EFA?
As explained by many already, it is better to perform both EFA and CFA. An exploratory factor analysis aims at exploring the relationships among the variables and does not have an a priori fixed number of factors.
What is the difference between CFA and EFA?
Exploratory factor analysis (EFA) could be described as orderly simplification of interrelated measures. By performing EFA, the underlying factor structure is identified. Confirmatory factor analysis (CFA) is a statistical technique used to verify the factor structure of a set of observed variables.
What’s the difference between a CFA and an EFA?
CFA and EFA are both methods of factor analysis. It is said that EFA extracts a factor structure from the data whereas CFA is used to test if a factor structure fits the data (or in other words to test a hypothesis). Given this, why would I want to do CFA instead of EFA if the latter is able to determine…
How does my confirmatory factor analysis ( CFA ) fit with my model?
“I take from your query that you were using the default confirmatory factor analysis (CFA) approach in Amos to fit your model. This uses maximum likelihood (ML) estimation which is *not appropriate* for the HLQ items. The HLQ items have 4 and 5 point ordinal response options.
Which is the best model fit statistic in CFA?
Model Fit Statistics The three main model fit indices in CFA are: Model chi-square this is the chi-square statistic we obtain from the maximum likelihood statistic (similar to the EFA) CFI is the comparative fit index – values can range between 0 and 1 (values greater than 0.90, conservatively 0.95 indicate good fit)
Which is the correct method for a CFA?
CFA (and exploratory factor analysis; EFA) of ordinal data with 4 and 5 point response options should be done with weighted least squares estimation and polychoric correlations* (the appropriate method for CFA is labelled WLSMV in Mplus and DWLS (diagonally-weighted least squares) in LISREL.