This example uses the
hsb2 data file to illustrate how to graph predicted probabilities against
a predictor variable with two interaction terms.
use https://stats.idre.ucla.edu/stat/stata/notes/hsb2, clear gen hon = (write>60) xi: logit hon i.female*math i.ses*math. xi: logit hon i.female*math i.ses*math, nolog Logistic regression Number of obs = 200 LR chi2(7) = 67.89 Prob > chi2 = 0.0000 Log likelihood = -77.408332 Pseudo R2 = 0.3049 ------------------------------------------------------------------------------ hon | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- _Ifemale_1 | -1.893752 3.340903 -0.57 0.571 -8.441802 4.654298 math | .1195186 .0702875 1.70 0.089 -.0182424 .2572797 _IfemXmath_1 | .0493777 .0582462 0.85 0.397 -.0647827 .1635382 _Ises_2 | -.8678234 3.984084 -0.22 0.828 -8.676484 6.940837 _Ises_3 | -1.761901 4.431971 -0.40 0.691 -10.44841 6.924603 _IsesXmath_2 | .0077363 .0718919 0.11 0.914 -.1331693 .1486419 _IsesXmath_3 | .0397258 .0785011 0.51 0.613 -.1141335 .1935851 _cons | -8.2049 3.886223 -2.11 0.035 -15.82176 -.5880425 ------------------------------------------------------------------------------preserve *for female = 0 gen yhat1 = _b[_cons] + math*_b[math] /* ses ==1 */ gen p1 = exp(yhat1)/(1+exp(yhat1)) gen yhat2 = _b[_cons] + math*_b[math] + _b[_Ises_2] + math*_b[_IsesXmath_2] /* ses ==2 */ gen p2 = exp(yhat2)/(1+exp(yhat2)) gen yhat3 = _b[_cons] + math*_b[math] + _b[_Ises_3] + math*_b[_IsesXmath_3] /* ses ==3 */ gen p3 = exp(yhat3)/(1+exp(yhat3)) sort math twoway (line p1 math) (line p2 math) (line p3 math), name(female1, replace)restore preserve *for female = 1 gen yhat1 = _b[_cons] + math*_b[math] +_b[_Ifemale_1] /* ses ==1 */ gen p1 = exp(yhat1)/(1+exp(yhat1)) gen yhat2 = _b[_cons] + math*_b[math] + _b[_Ises_2] + math*_b[_IsesXmath_2] /// + _b[_Ifemale_1] + math*_b[_IfemXmath_1] /* ses ==2 */ gen p2 = exp(yhat2)/(1+exp(yhat2)) gen yhat3 = _b[_cons] + math*_b[math] + _b[_Ises_3] + math*_b[_IsesXmath_3] /// + _b[_Ifemale_1] + math*_b[_IfemXmath_1] /* ses ==3 */ gen p3 = exp(yhat3)/(1+exp(yhat3)) sort math twoway (line p1 math) (line p2 math) (line p3 math) , name(female2, replace)
restore