We have a data set from N=193 participants. They assessed Corporate Image, Employer Image, Customer Experience and Employer Attractiveness (on Likert scales) for 8 different companies (each of the participants assessed all 8 companies). Employer Attractiveness is the DV. We ran regression for the total of 193*8 = 1544 observations to identify which of the IDVs (Corporate Image, Employer Image, Customer Satisfaction) has the largest impact on Employer Attractiveness (which is our research question). Now feedback of reviewers is mixed and irritating. One says, we must run a SEM in order to discern impact strength of the IDVs. Another says, we should apply a repeated-measures/within-subjects design. Can anybody help?
Hermann Lassleben Based on the comments, your work might have some latent variable.
Good luck.
Firstly, the research point is very excellent, and I wish you good luck with it. Secondly, you must check the distribution of the data, is it a normal distribution or not?, so that you can use the appropriate test, whether it is a parametric test or a nonparametric one. One of the most important methods that need to be used is SEM (Structure Equation Modelling) by the AMOS software (Within SPSS software), in addition, you can use a variance analysis. I totally agree with the opinion of the arbitrator using SEM.
Hermann Lassleben Based on the comments, your work might have some latent variable.
Good luck.
First when you ran the regression what were your r values? b or Beta values? that is where you should be heading...
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