Dear all,
I am trying to estimate marginal effects and predicted probabilities for a multilevel (logistic) analysis, treated with multiple imputation procedures. I have been able to get the linear predictions as outlined in the reference manual. However, after reading several posts on obtaining predicted probabilities, none of the commands appear to work.
I have attempted to use both predict( outcome(#)) and predict(pr) in the command line, however, neither option is allowed. My code is as such:
*N.B. I cite cmdmargins to allow for marginsplot*
Both commands, however, return the r(198) error that such an option is not allowed.
Is there a way to obtain these predicted probabilities? Any suggestions would be much appreciated.
Apologies for any inconvenience.
Kind Regards,
Patrick
I am trying to estimate marginal effects and predicted probabilities for a multilevel (logistic) analysis, treated with multiple imputation procedures. I have been able to get the linear predictions as outlined in the reference manual. However, after reading several posts on obtaining predicted probabilities, none of the commands appear to work.
I have attempted to use both predict( outcome(#)) and predict(pr) in the command line, however, neither option is allowed. My code is as such:
Code:
mi estimate, dots or: meqrlogit mviolence ib(6).age ib(1).nordic ib(3).incomeq ib(4).famdec cen_gii cen_unempg ib(1).partneremp(cen_sprotect cen_womeduc) || country: mimrgns, predict(outcome(1)) at(partneremp=(0 1 2) cen_sprotect=(-544.1996 -272.0998 0 272.0988 544.1996)) cmdmargins
Code:
mi estimate, dots or: meqrlogit mviolence ib(6).age ib(1).nordic ib(3).incomeq ib(4).famdec cen_gii cen_unempg ib(1).partneremp(cen_sprotect cen_womeduc) || country: mimrgns, at(partneremp=(0 1 2) cen_sprotect=(-544.1996 -272.0998 0 272.0988 544.1996)) /// predict(pr) cmdmargins
Both commands, however, return the r(198) error that such an option is not allowed.
Is there a way to obtain these predicted probabilities? Any suggestions would be much appreciated.
Apologies for any inconvenience.
Kind Regards,
Patrick
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