Dear STATA users,

I would much appreciate your help with my analysis which goes as follows:

I run mlogit using multiply chained imputed data:

Code:
mi set mlong

mi register imputed volba migranti_squared lidr i_prijmu migranti_2011 egal egalitarstvi euroskepticismus_rek populismus apatie narodovectvi subjektivni_politicka_kompetence status vzdelani_rek pohlavi_rek vek_rek bydliste_2kat religiozita_rek cynismus

mi impute chained (mlogit) volba (regress) migranti_squared (regress) lidr (regress) i_prijmu (regress) migranti_2011 (regress) egal (regress) egalitarstvi (regress) euroskepticismus_rek (regress) populismus (regress) apatie (regress) narodovectvi (regress) subjektivni_politicka_kompetence (regress) status (regress) vzdelani_rek (mlogit) pohlavi_rek (regress) vek_rek (mlogit) bydliste_2kat (mlogit) religiozita_rek (regress) cynismus, add(10) rseed (54321) savetrace (trace1, replace)

mi estimate, dots: mlogit volba migranti_squared lidr i_prijmu migranti_2011 egal egalitarstvi euroskepticismus_rek populismus apatie narodovectvi subjektivni_politicka_kompetence status vzdelani_rek i.pohlavi_rek vek_rek i.bydliste_2kat i.religiozita_rek cynismus [pweight= VAHA], base (1)
Then I want to create marginsplot to plot predictive margins by independent variable "euroskepticismus_rek" (values 0 to 10) for each category of my dependent variable "volba" (3 categories - 1,2,3)
I am using mimrgns command:

Code:
mimrgns, at (euroskepticismus_rek = (0 (1) 10)) predict(pr) cmdmargins vsquish
marginsplot, noci scheme(sj) name(mimrgnsplot)
Array

I am able to get the plot of predictive margins (see the picture above) for the first category of dependent variable (which is set as a base category in mlogit).
Is there a way to modify my code so it creates the same plot for every category of my dependent variable?
Thank you in advance for any suggestions.