Dear all,
I trust this email finds you well.
I am currently testing a theorical model using the PLS-SEM and Smartpls. The aim is to assess the influence of certain soft skills (empathy) on client relationship outcomes (e.g customer loyalty).
I would like to control to assess the effect of certain (control) variable on some of my dependent variables.
The issue that I am encountering is the following.
I have 5 control variables:
· Gender (w/ 2 groups: male female)
· Salary (w/ 5 groups: below 20k, 21-30k, 31-50k, 51-70k, +70k)
· Education (w/ 5 groups: no diploma, high school diploma, bachelor, master, PhD)
· Visit frequency (w/ 5 groups: once a year, once every 6 months, ect...)
If I understood things correctly to yield significant result and interpret findings correctly, I will need to use dummy variables. Which means that, based on the above, there will be a total of 17 control variables.
Based on your experience, is there a way to simplify the above? I was thinking to reduce the number of groups for each variable. For instance, instead of having 5 salary categories, reduce the number of categories down to 2 such as:
- Salary: above and below the national average salary.
- Education: those who have at least a master, those who do not.
Etc…
What do you think of the above?
Of course, if you have any information / resources / material / that may allow me to address the above issue, that will be appreciated.
I thank you once more for your assistance and wish you a nice day.
Best regards,
Axel Tedesco, since you are using these variables as control variables and they are ordered, it is definitely better to use these as quasi-continuous variables in your regression model instead of creating unnecessarily many dummies or even worse, dichotomising them.
Axel Tedesco, considering you will use latent variables to measure the effects of the control variables, and indicators are grouped to create a composite latent variable, the number of indicators per latent variable is not a problem. Remember to set control latent variables as formative.
Hope my suggestions help you,
Alexandre
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