Extremely helpful. I was looking everywhere to find out how control variables in Smart-PLS, and was getting depressed as I wasn't find out the exact one. Yours video saved my life.
sir why when i run the boostrap process, the result i get for the variables with more than 2 category (i.e. age) different category have different p value ( i.e 17-25 p=0.05, 25-35 p=0.4) not as age in general
thank you for the video! what if our control variable is in interval or ratio data? for example, our control variable is familiarity to AI measured in Likert scale 1-7?
Thanks, this video is really helpful. In different references, it's discouraged to use dummy variables for PLS-SEM model construction. Is there any statistical limitation or comparative drawback using dummy/binary variables in PLS-SEM modelling?
www.emerald.com/insight/content/doi/10.1108/IMDS-09-2015-0382/full/html in this paper you will find details of why it is important to make dummy variables. Sometimes we have categorical predictors in our framework as well. Although the general practice is to make IVs and DVs as continuous variables while testing for control/demographic variables before we test the strucural model. In that case binary/dummy variables are useful .
Greetings sir incase we have moderator and mediator in my model control variable will be assessed with only ultimate dependent variable or moderator and mediator as well?
both options can be adopted majority studies does this with main dependent variable but it is recommended that you do with any variable that is dependent in the model
excellent presentation, you solved my problem thanks alot. please provide the full references of the sources you cited in your tutorial. i will be indebted to you.
Extremely helpful. I was looking everywhere to find out how control variables in Smart-PLS, and was getting depressed as I wasn't find out the exact one. Yours video saved my life.
sir why when i run the boostrap process, the result i get for the variables with more than 2 category (i.e. age) different category have different p value ( i.e 17-25 p=0.05, 25-35 p=0.4) not as age in general
thank you for the video! what if our control variable is in interval or ratio data? for example, our control variable is familiarity to AI measured in Likert scale 1-7?
Thanks, this video is really helpful. In different references, it's discouraged to use dummy variables for PLS-SEM model construction. Is there any statistical limitation or comparative drawback using dummy/binary variables in PLS-SEM modelling?
www.emerald.com/insight/content/doi/10.1108/IMDS-09-2015-0382/full/html
in this paper you will find details of why it is important to make dummy variables. Sometimes we have categorical predictors in our framework as well. Although the general practice is to make IVs and DVs as continuous variables while testing for control/demographic variables before we test the strucural model. In that case binary/dummy variables are useful .
you can use dummy variable function in spss
Greetings sir incase we have moderator and mediator in my model control variable will be assessed with only ultimate dependent variable or moderator and mediator as well?
both options can be adopted
majority studies does this with main dependent variable but it is recommended that you do with any variable that is dependent in the model
@@FacilitatorFarhan ok thank you
excellent presentation, you solved my problem thanks alot. please provide the full references of the sources you cited in your tutorial. i will be indebted to you.
www.emerald.com/insight/content/doi/10.1108/IMDS-09-2015-0382/full/html
this paper explains how to include cateogrical control variable in the model
sir, I am not able to apply this formula, can you help