I'm not completely sure what your end goal is, but it wounds like you are trying to reproduce the results of a prior study that examined the factor structure of some questionnaire.

If this is what you are trying to do, you can do one of three things:

1. Simply run an EFA using the same oblique or orthogonal rotation again and see if it gives similar results. This is probably the least preferable method, but regardless it seems to be the most common approach in behavior science literature. (As such, this might be the easiest to publish approach.)

2. Run an EFA using a target rotation - This is really a confirmatory EFA. EFA basically refers to a technique that involves rotating a correlation matrix. In a target rotation, you simply tell the software how you want it to rotate the correlation matrix, and it attempts to rotate the to get as close a solution as possible to what you gave it.

3. Run a Confirmatory Factor Analysis using the factor structure that the EFA showed. Unlike EFA, CFA does not involve matrix rotation, and will fit the model you specify (rather than trying to get close). You might find a that the model you specify has terrible fit or you might find good fit.

Hope this is helpful. If you need software, R has the psych and GPArotation packages that can help with EFA (including a target rotation). For the CFA, lavaan is probably the most user friendly.

Yes, Paul's explanation makes sense.

One can also use SPSS, and other software too,

Joeri can also verify the difference (if any) between previous result and the result if it done afresh, in the new context/ space. That itself may also provide answer to the question.

I concur with Paul and Rabinarayan. I would definitely use CFA to test the proposed factor structure, i.e., Pauls suggestion 3. CFA will give you an estimate of the fit between observed data and the proposed model and the probability of dispersion using Chi-squared test. However, if you find that the fit is poor, then you can use EFA to find an alternative factor structure. Then, you can test this factor structure on a new dataset using CFA. There are several computer programs for CFA. I use LISREL, but if you are using SPSS you would probably prefer their “add-on” Amos. Then you have R, Mplus (probably one of the best) etc. Good luck with the analyses!

I also concur.  You can't really use the same factor loadings in a new data set, but should run a CFA -- or forego factor loadings and just use unweighted scores.  But, if you have an adequate sample size, a CFA will tell you many things -- (a) do the items actually load on the same factors; (b) are the loadings the same; (c) are the means the same; and (d) are the variances the same.  But if you don't have an adequate sample size, then just use the unweighted factor structure.  Good luck!

Thanks everyone. I am a little bit out of my comfort zone here, but I have downloaded  AMOS and am about to give it a try. Your help has been much appreciated.