[Gretl-users] Sloeps in Probit and Logit when independent variables are discrete

Dear All I found that gretl provides a nice "slope" feature in Probit and Logit models. However, when independent variables are discrete, gretl computes slopes as they are continuous variables. I compare gretl's result with other packages, such as STATA and Matlab (the Probit output produced by Matlab are attached below) They will automatically detect the discrete variables in Probit (as well as in Logit) to compute the slope (also named as marginal effects) and mark them in a footnote: "(*) dy/dx is for discrete change of dummy variable from 0 to 1." Do you think our gretl should do the same thing? Thanks Yi-Nung ===MATLAB output === Probit Regression Regressor Coefficient Std. Error t-stat Prob>|t| ------------------------------------------------------------------ constant -2.81108 0.65883 -4.26678 0.00002 variable1 0.00159 0.00064 2.47531 0.01373 variable2* 0.27799 0.18129 1.53338 0.12599 variable3 0.36204 0.19664 1.84112 0.06636 variable4 0.00041 0.00024 1.70164 0.08961 variable5* -0.12469 0.13433 -0.92821 0.35387 variable6* -0.07526 0.13467 -0.55887 0.57657 ------------------------------------------------------------------ (*) indicates that the variable is a dummy Marginal Effect Regressor Marginal Std. Error t-stat Prob>|t| ------------------------------------------------------------------ variable1 0.00056 0.00023 2.48203 0.01348 variable2* 0.10175 0.06855 1.48438 0.13851 variable3 0.12732 0.06907 1.84341 0.06602 variable4 0.00014 0.00008 1.70222 0.08951 variable5* -0.04386 0.04722 -0.92888 0.35352 variable6* -0.02648 0.04739 -0.55876 0.57665 ------------------------------------------------------------------ (*) dy/dx is for discrete change of dummy variable from 0 to 1.