Difference between control variables and moderating variables
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- PLS Junior User
- Posts: 1
- Joined: Thu Oct 05, 2023 12:54 pm
- Real name and title: Ms. Palak Mittal
Difference between control variables and moderating variables
I am using demographic variables such as age, gender, income, area in my study. According to me these are moderators but on reading various research papers related to Smart PlS, I got to know that these are used as control variables. I can't find out what is the difference between the two and which one should I use?
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- SmartPLS Developer
- Posts: 1287
- Joined: Tue Mar 28, 2006 11:09 am
- Real name and title: Dr. Jan-Michael Becker
Re: Difference between control variables and moderating variables
A moderator variable Z influence the strength of a relationship between two variables X and Y.
The estimated effect of X on Y is conditional on Z (being equal to zero).
For example, income may be a moderator of the relationship between satisfaction and loyalty: with higher (lower) income the relationship between satisfaction and loyalty might be stronger (weaker).
A control variable Z should ensure that the relationships between X and Y is not influenced by the variation in the control variable Z.
In other words, it helps researchers rule out the possibility that changes in the dependent variable Y are due to changes in the control variable Z rather than the independent variable X.
The estimated effect of X on Y is the unconditional effect of keeping Z constant at any value.
For example, the estimated effect of satisfaction on loyalty for people with equal income.
The estimated effect of X on Y is conditional on Z (being equal to zero).
For example, income may be a moderator of the relationship between satisfaction and loyalty: with higher (lower) income the relationship between satisfaction and loyalty might be stronger (weaker).
A control variable Z should ensure that the relationships between X and Y is not influenced by the variation in the control variable Z.
In other words, it helps researchers rule out the possibility that changes in the dependent variable Y are due to changes in the control variable Z rather than the independent variable X.
The estimated effect of X on Y is the unconditional effect of keeping Z constant at any value.
For example, the estimated effect of satisfaction on loyalty for people with equal income.
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de