Control Variables

[Isaac F]

Hello, 

I am using 5 control variables in my model. They are linked directly to all endogenous variables in the model. How should I analyse and report their impact? 
1. should I report first on the R2 value of the endogenous variable and then connect the predictors and see if the R2 have increased? 
2. should I include them in the model even if their path coefficient is less than 0.1 and they are non significant? 

Thanks,

[Ned Kock]

You may find these links useful:

Article: Kock, N. (2011), Using WarpPLS in e-collaboration studies: Mediating effects, control and second order variables, and algorithm choices. International Journal of e-Collaboration, 7(3), 1-13.

http://www.scriptwarp.com/warppls/pubs/Kock_2011_IJeC_WarpPLSEcollab3.pdf

Blog post:

http://warppls.blogspot.com/2010/02/how-do-i-control-for-effects-of-one-or.html

Dr. Moqbel's dissertation:

http://www.scriptwarp.com/warppls/pubs/Moqbel_2012_PhDDiss_Redirect.pdf

[Isaac F]

Thank you Ned, this is very useful indeed,

However, I could'f find a justification for your recommendation to ignore the significance of the CV paths (i.e. the effect of the control variable on the endogenous variable). Can you please refer me to some relevant references or provide me an explanation of why the significance in this case is not important? I would really appreciate that,

Best,

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[V G Venkatesh]

Hi Professor,

In treating control variables in WarpPLS, i am getting  increased R2 (0.42 to 0.50) values after adding two control variables. 

How should we interpret the same ?

Regards

VG 

[Ned Kock]

Hi VG. This is actually quite common. The more variables (e.g., A, B, C etc.) point at a variable Z, the greater is usually the explained variance in Z by those variables A, B, C etc.

On Wednesday, August 23, 2017 at 7:11:59 AM UTC-5, V G Venkatesh wrote:

Hi Professor,

In treating control variables in WarpPLS, i am getting  increased R2 (0.42 to 0.50) values after adding two control variables. 

How should we interpret the same ?

[...]

[V G Venkatesh]

Thanks Professor.

If the control variable shows the negative to the dependent variables (the ideal expected relationship is positive), is it ok to leave like that ? 

Yes, the overall paths (for hypothesized relationships) remain same without getting affected by the inclusion of control variables.

Appreciate your explnation on this. 

Thanks

VG