If we are aiming to study the impact of an independent variable X on Y and on Z.
At the same time, we want to study the impact of Y on Z.
So the relationships to be studied are :
Effect of X on Y
Effect of X on Z
Effect of Y on Z
Each is in a single research question.
The data of the 3 variables is ordinal (non-parametric), so ordinal regression is the selected test for the 3 research questions according to Cohen's book.
My question:
If I think that Y might be the mediating variable, should I put this as a research question? Like: Does Y mediate the relationship between X and Z?
If so, what is the correct statistical test for this question?
I thought of multiple regression, but here X and Y might be highly correlated (according to literature), and I read that multiple regression is not suitable in this case.
Hello Nour,
Given that you are expressing an interest in whether mediation of X on Z via Y is occurring, I'd suggest that running three separate, bivariate regressions (e.g., X & Y as IV and DV, respectively) is not the best path. Instead, evaluating the full model via path analysis would be preferred. Your interest is in the relative magnitude of the indirect effect (X->Y * Y->Z) vs. the direct effect (X->Z).
The Mplus package is well-known for having ordinal data handling capability. Others, like the free lavaan library in R, can handle ordinal DVs (I can't remember if the IVs can be ordinal, or have to be recast as dummy variates; see this explication by the author of lavaan: https://personality-project.org/r/tutorials/summerschool.14/rosseel_sem_cat.pdf)
Good luck with your work.
@Nour Salim Whether you want yo check mediation effect of Y or not, you still should go for SEM/Path Analysis. If you have theory support for the mediation effect of Y, then go for it and check the mediation as well.
Nour Salim , I suggest Bayesian Networks, a mathematically more elegant approach:
https://en.wikipedia.org/wiki/Bayesian_network#:~:text=A%20Bayesian%20network%20(also%20known,directed%20acyclic%20graph%20(DAG).
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