"As i have small data set, so i will have to use SPSS to analyse the data. " What's the relation between using a software and sample size?

I get that it's a pilot study, but 28 responses is very small for you to have results you can trust before going further. Trying going up to 50-100, especially for factor analysis, and especially if the structure is complex (more latent constructs to estimate needs more data to estimate them, basically).

Anyway, here's something more practical, see answers to this question on RG.

https://www.researchgate.net/post/How_can_I_perform_second_order_factor_analysis_in_SPSS/1

Hi Nils,

Thanks, this is very useful link. 

Rule of thumb is that you need at least 100 subjects to conduct EFA or five subjects per variable - especially if you have latent constructs (see Gorsuch). Hope this helps

Also Are you trying to build a Path Model ?

SmartPLS will help you in this case, in case of less data points. Also Its easy to build 2nd order constructs...

Hi Julie, 

Thanks. It helps but i have only 28, So, nither way the rule of thumb is ok for me. But your answer helps me decide the next step. 

Thanks. 

With that sample size, try with Partial least squares -SEM (PLS-SEM).

Abdul,

While I concur with others that a bigger sample size would be preferred, let me answer your question.

You have two options using SPSS; each presumes that you used an oblique rotation (e.g., Promax or Oblimin) for final factor solution:

1. WIthin the SPSS factor analysis, there is the option to create and save factor scores for each case to your worksheet.  Do this.  Then, run a second factor analysis, using the three factor scores as the variables to be factored.

2. Enter the summary correlations among the three factors using syntax similar to that below (for a 3-variable problem), then run the factor subprogram (again, using syntax).

If you have the AMOS add-on, you can directly specify higher-order factors, but the default context is CFA, not EFA.

Good luck with your study!

David Morse

MATRIX DATA VARIABLES = x1 x2 x3

  /FILE= INLINE

  /FORMAT= LOWER DIAG

  /CONTENTS=corr N .

begin data

1.0

0.64 1.0

0.48 0.48 1.0

100 100 100

end data.

factor

/matrix = in(cor = *)

/ extraction = ml

/ rotation = oblimin

/ print = default correlation kmo aic repr

/ plot = eigen .

Dear David, 

Thank you so much. You actually provided a step by step guidelines. Thanks. It is helpful. 

Regards, 

Abdul