Dear Members,
I am having a little bit of trouble in interpreting interaction effects between dummies in the context of a logit model.
I have logit model where dependent variable Y is probability of being in favour of animal cloning, then I have a categorical independent variable support ranking support for government on a 1-4 scale, and female which is a dummy for gender (female=1, male=0), plus controls. I am interested in looking at interaction effects between support and female with respect to Y.
There's two main points to my question.
A)
Now, in the context of a non-linear model, I am aware that interpreting interaction effects has been the subject of a big debate essentially between two options:
1) using -inteff- command, (Norton, Wang and Ai, 2004)
2) using -margins- which is a more up-to-date version with respect to -mfx- and should take care of the issues that -inteff- was originally set up for
----I am struggling to understand what would be the best approach to go for, is -margins- yielding misleading estimates of both size and direction of the interaction's ME or is it just less accurate or what?
B)
In order to circumvent the issue above, I opted to create dummies for each category of support:
support1=1 when an individual has level of support=1
support2=1 when an individual has level of support=2
support3=1 when an individual has level of support=3
support4=1 when an individual has level of support=4
Then I manually created the interaction effects with female:
support1fem = support1*female
support2fem = support2*female
support3fem = support3*female
support4fem = support4*female
All of these four newly created variable should, in theory, be dummies themselves since they can only ever take value of 0 or zero (they are the products of two dummies)
I then run the regression:
logit support2 support3 support4 female support2fem support3fem support4fem
(support1 is the default group)
And computed marginal effects with -margins, dydx(*) atmeans- command. I am then interpreting, for example in the case of the support2fem interaction variable, their ME as being "the over and above effect of being female on the probability that Y=1, given a level 2 support category" (compared to a male with a level 1 support category).
Am I interpreting this correctly by using -margins- on manually computed interaction terms between two dummies?
Thank you so much for your help in advance!
I am having a little bit of trouble in interpreting interaction effects between dummies in the context of a logit model.
I have logit model where dependent variable Y is probability of being in favour of animal cloning, then I have a categorical independent variable support ranking support for government on a 1-4 scale, and female which is a dummy for gender (female=1, male=0), plus controls. I am interested in looking at interaction effects between support and female with respect to Y.
There's two main points to my question.
A)
Now, in the context of a non-linear model, I am aware that interpreting interaction effects has been the subject of a big debate essentially between two options:
1) using -inteff- command, (Norton, Wang and Ai, 2004)
2) using -margins- which is a more up-to-date version with respect to -mfx- and should take care of the issues that -inteff- was originally set up for
----I am struggling to understand what would be the best approach to go for, is -margins- yielding misleading estimates of both size and direction of the interaction's ME or is it just less accurate or what?
B)
In order to circumvent the issue above, I opted to create dummies for each category of support:
support1=1 when an individual has level of support=1
support2=1 when an individual has level of support=2
support3=1 when an individual has level of support=3
support4=1 when an individual has level of support=4
Then I manually created the interaction effects with female:
support1fem = support1*female
support2fem = support2*female
support3fem = support3*female
support4fem = support4*female
All of these four newly created variable should, in theory, be dummies themselves since they can only ever take value of 0 or zero (they are the products of two dummies)
I then run the regression:
logit support2 support3 support4 female support2fem support3fem support4fem
(support1 is the default group)
And computed marginal effects with -margins, dydx(*) atmeans- command. I am then interpreting, for example in the case of the support2fem interaction variable, their ME as being "the over and above effect of being female on the probability that Y=1, given a level 2 support category" (compared to a male with a level 1 support category).
Am I interpreting this correctly by using -margins- on manually computed interaction terms between two dummies?
Thank you so much for your help in advance!
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