HuiGuo Liu posted on Wednesday, April 15, 2009 - 6:40 am
I remember that I have read somewhere about the number of observations needed to do CFA/EFA for categorical data.
It sounds like that as long as any number of observations of the 2 by 2 matrix generated by any two of the items/variables is larger than 5, categorical CFA/EFA is suitable.
And in that statement, there is also an exmple following to show that even sometimes the whole number of observations is not very large, categorical EFA/CFA could be performed since the required condition is not demanding at all.
I cannot remember where I have read that and whether this is a correct statement.
In general, you need more observations for categorical data than for continuous data. The only way to know how large a sample is needed in any particular situation is to do a Monte Carlo study. See the following reference:
Muthén, L.K. & Muthén, B.O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling, 4, 599-620.
HuiGuo Liu posted on Tuesday, April 21, 2009 - 2:55 pm
Thanks a lot of the response.
I saw the paper at a quick glance,and found that the CFA examples it used were all with continuous outcomes. But my own research is with 20 ordered variables. I just wonder are the test method and conclusion from the examples also applicable to my own research?