I have collected data using questionnaires from athletes at two time points. I have an independent variable (leadership) and a few dependent variables but also some mediating or indirect variables such as trust ect. All of the variables were measured using the same questionnaire at two time points.
What data analysis method would be best to analyse the data? So far I have used the Process macro on SPSS which uses OLS regressions but I am unsure if this is the best method.
I essentially want to see how the IV relates/ increases the dependant variables over time and whether this changed occurred directly from the IV and indirectly through the mediators.
Would these be appropriate research questions for the type of data I have and for the appropriate analysis technique?
Hello Ella,
The "best" analysis will depend on: (a) your specific research question/s; (b) the nature of the variables that you have collected and how they are quantified; and (c) your sampling procedures. You may find that an SEM framework would be easier for expressing your hypothesized model of how the variables do or don't fit together (even though Hayes' PROCESS add-in is pretty darn versatile). But, your query isn't fully elaborated, so (as an example) I have no way to judge whether you'd be better off with a univariate vs. a multivariate approach.
It sounds as if it might be worth your while to chat with someone from your institution to help arrive at an analytic approach that would answer your specific questions (a, above), while being defensible (given b and c, above).
Good luck with your work!
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