My dependent variable is binary, so is one of my two independent variables. The other Ind Var is ordinal, ranging from 1 to 10.
Both independent variables have a significant impact when I run a probit/logit/ or even OLS.
Now, I'm interested in the interaction effect.
For this, I currently compare the average marginal effect of X2 when my binary independent variable, X1, either takes the value of 0 or the value of 1.
Code:
probit Y X1##X2, vce(cluster id) robust margins, dydx (c.X2) at (X1=(0 1))
I would like now to say more about the difference, whether the difference is significant.
This can not be done through 'inteff', as I get the error factor-variable and time-series operators not allowed and I
I have browsed through the list, read multiple papers such as https://journals.sagepub.com/doi/pdf...867X1201200209 (Richard Williams, 2012), https://www3.nd.edu/~rwilliam/stats/Margins01.pdf (Richard Williams, 2020), and earlier work on LDV techniques by Bowen & Wiersema or Norton, Wang & Ai.
Yet, it seems as if this problem has not been solved/addressed yet?
Thank you for any insight!
0 Response to Interaction effect in probit/logit significant?
Post a Comment