moderator effect

[hussein bataineh]

Hi

please im trying to see the moderator effect of ( CSR_Committee) it is a dummy variable (1 ,0 )


Where
moderator effect of ( CSR_Committee) it is a dummy variable (1 ,0 )
Dependent variable EQUITY continuous variable
Independent variable is CSO is a dummy variable (1 ,0 )
control variables FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR Governance_Score_w SustainabilityScore_w CSR_Committee

i code the model as followings

my model is as following

reg EQUITY CSO FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR Governance_Score_w SustainabilityScore_w CSR_Committee i.CSO#i.CSR_Committee



But it give when i run the regression


. reg EQUITY CSO FSIZE OP_CF SD_OCF TAX BM LEV MA DPP RPP PSIZE DR Governance_Score_w SustainabilityScore_w
> CSR_Committee i.CSO#i.CSR_Committee
note: 1.CSO#0b.CSR_Committee omitted because of collinearity.
note: 1.CSO#1.CSR_Committee omitted because of collinearity.


in the regression

CSO#CSR_Committee |
CSO Not Present#1 | -3.001053 1.538676 -1.95 0.051 -6.017678 .0155724
CSO Present#0 | 0 (omitted)
CSO Present#1 | 0 (omitted)

[Clyde Schechter]

I see nothing obviously wrong with the code. Apparently there is some colinearity in your regressor variables involving levels of the CSO#CSR_Committee interaction. So the problem must arise in the data itself. As you do not provide example data, there is little more that can be said.

If you use the -dataex- command to post example data here, it should be possible to identify more specifically the source of the problem. If you do that, be sure your example includes observations representing all four combinations of CSO and CSR_Committee, and includes all variables mentioned in the -reg- command.

If you are running version 18, 17, 16 or a fully updated version 15.1 or 14.2, -dataex- is already part of your official Stata installation. If not, run -ssc install dataex- to get it. Either way, run -help dataex- to read the simple instructions for using it. -dataex- will save you time; it is easier and quicker than typing out tables. It includes complete information about aspects of the data that are often critical to answering your question but cannot be seen from tabular displays or screenshots. It also makes it possible for those who want to help you to create a faithful representation of your example to try out their code, which in turn makes it more likely that their answer will actually work in your data.