logit_cc {DAMisc}  R Documentation 
Norton and Ai (2003) and Norton, Wang and Ai (2004) discuss methods for
calculating the appropriate marginal effects for interactions in binary
logit/probit models. These functions are direct translations of the Norton,
Wang and Ai (2004) Stata code. These functions are not intended to be
called by the user directly, rather they are called as needed by
intEff
.
logit_cc(obj = obj, int.var = int.var, vars = vars, b = b, X = X)
obj 
A binary logit or probit model estimated with 
int.var 
The name of the interaction variable. 
vars 
A vector of the two variables involved in the interaction. 
b 
Coefficients from the 
X 
Model matrix from the 
A data frame with the following variable:
int_eff 
The correctly calucalted marginal effect. 
linear 
The incorrectly calculated marginal effect following the linear model analogy. 
phat 
Predicted Pr(Y=1X). 
se_int_eff 
Standard error of

zstat 
The interaction effect divided by its standard error 
Dave Armstrong
Norton, Edward C., Hua Wang and Chunrong Ai. 2004. Computing
Interaction Effects and Standard Errors in Logit and Probit Models. The
Stata Journal 4(2): 154167.
Ai, Chunrong and Edward C. Norton. 2003. Interaction Terms in Logit and Probit Models. Economics Letters 80(1): 123129.
Norton, Edward C., Hua Wang and Chunrong Ai. 2004. inteff: Computing Interaction Effects and Standard Errors in Logit and Probit Models, Stata Code.