I hope you had a merry Christmas.
Currently I face difficulties on how to pairwise t-test a three-way interaction in order to understand which slopes are different from each other. However, I could not find a post with the same issue. Without interaction effects, the <test> command seems to work for slope comparisons but I failed to properly specify the command.
Example: Let's assume we have a basic three-way interaction in a tobit model with a three-way interaction among A, B, and C using robust standard errors clustered by D.
Code:
tobit Y c.A##B##C, vce(cluster D) ll(0)
Code:
margins, dydx(A) at(B=(0 1) C=(0 1))
. margins, dydx(LBooktomarket) at(LFF_UO_lar5to50=(0 1) LFF_UO_Mgmt=(0 1))
Average marginal effects Number of obs = 3,194
Model VCE : Robust
Expression : Linear prediction, predict()
dy/dx w.r.t. : LBooktomarket
1._at : LFF_UO_Mgmt = 0
LFF_U~r5to50 = 0
2._at : LFF_UO_Mgmt = 0
LFF_U~r5to50 = 1
3._at : LFF_UO_Mgmt = 1
LFF_U~r5to50 = 0
4._at : LFF_UO_Mgmt = 1
LFF_U~r5to50 = 1
-------------------------------------------------------------------------------
| Delta-method
| dy/dx Std. Err. t P>|t| [95% Conf. Interval]
--------------+----------------------------------------------------------------
LBooktomarket |
_at |
1 | -.0013346 .0033915 -0.39 0.694 -.0079844 .0053151
2 | .0323928 .0168608 1.92 0.055 -.0006666 .0654522
3 | .0233028 .0114768 2.03 0.042 .0007999 .0458057
4 | .0050212 .0143031 0.35 0.726 -.0230232 .0330657
-------------------------------------------------------------------------------
Average marginal effects Number of obs = 3,194
Model VCE : Robust
Expression : Linear prediction, predict()
dy/dx w.r.t. : LBooktomarket
1._at : LFF_UO_Mgmt = 0
LFF_U~r5to50 = 0
2._at : LFF_UO_Mgmt = 0
LFF_U~r5to50 = 1
3._at : LFF_UO_Mgmt = 1
LFF_U~r5to50 = 0
4._at : LFF_UO_Mgmt = 1
LFF_U~r5to50 = 1
-------------------------------------------------------------------------------
| Delta-method
| dy/dx Std. Err. t P>|t| [95% Conf. Interval]
--------------+----------------------------------------------------------------
LBooktomarket |
_at |
1 | -.0013346 .0033915 -0.39 0.694 -.0079844 .0053151
2 | .0323928 .0168608 1.92 0.055 -.0006666 .0654522
3 | .0233028 .0114768 2.03 0.042 .0007999 .0458057
4 | .0050212 .0143031 0.35 0.726 -.0230232 .0330657
-------------------------------------------------------------------------------
Thank you very much.
Best,
Martin
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