Hi all,
I'm trying to figure out a way to use the suest and test command (or something similar) after multiple imputation.
I am running some stratified multiple regression models where I am using the suest and the posestimation "test" command to see if the relationship between my DV and IV is significantly different across my two subsamples (first-gen students and continuing-gen students). Prior to multiple imputation, I had been using the suest command followed by the test command to accomplish this with the following code:
This gives me what I'm looking for with no issues. However, I used multiple imputation on this dataset to deal with missing cases and I'm trying to accomplish the same thing as above, just with imputed data. I still want to test to see if the relationship between my DV and IV is significantly different across different subsamples. When I run the following code, I get an error message from Stata:
The error message I'm getting is:
mi estimate: command not supported
suest is not officially supported by mi estimate; see mi estimation for a list of Stata estimation commands that are supported by mi estimate. You
can use option cmdok to allow estimation anyway.
r(198);
I have tried to use the cmdok option and I get another error message that states:
impossible to retrieve e(b) and e(V_modelbased) in cgen2
an error occurred when mi estimate executed suest on m=1
r(198);
I essentially just need to be able to test to see whether the differences in the coefficients for the "singleparent" variable between continuing-gen and first-gen students are significant. Any help on this is much appreciated!
I'm trying to figure out a way to use the suest and test command (or something similar) after multiple imputation.
I am running some stratified multiple regression models where I am using the suest and the posestimation "test" command to see if the relationship between my DV and IV is significantly different across my two subsamples (first-gen students and continuing-gen students). Prior to multiple imputation, I had been using the suest command followed by the test command to accomplish this with the following code:
Code:
logit everenrollcollege bioguardian singleparent guardianonly twobioparent if firstgen==0 est sto cgen logit everenrollcollege bioguardian singleparent guardianonly twobioparent if firstgen==1 est sto fgen suest cgen fgen, vce(cluster schoolid) cformat(%9.3f) test [cgen_everenrollcollege]singleparent=[fgen_everenrollcollege]singleparent
Code:
mi estimate: logit everenrollcollege bioguardian singleparent guardianonly twobioparent if firstgen==0 est sto cgen mi estimate: logit everenrollcollege bioguardian singleparent guardianonly twobioparent if firstgen==1 est sto fgen mi estimate: suest cgen fgen, vce(cluster schoolid) cformat(%9.3f)
mi estimate: command not supported
suest is not officially supported by mi estimate; see mi estimation for a list of Stata estimation commands that are supported by mi estimate. You
can use option cmdok to allow estimation anyway.
r(198);
I have tried to use the cmdok option and I get another error message that states:
impossible to retrieve e(b) and e(V_modelbased) in cgen2
an error occurred when mi estimate executed suest on m=1
r(198);
I essentially just need to be able to test to see whether the differences in the coefficients for the "singleparent" variable between continuing-gen and first-gen students are significant. Any help on this is much appreciated!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(firstgen everenrollcollege bioguardian singleparent guardianonly twobioparent) 1 1 0 0 0 1 1 1 0 0 0 1 1 1 0 1 0 0 1 1 0 0 0 1 1 0 0 1 0 0 0 1 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 0 1 1 0 0 0 1 1 1 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 1 0 0 0 0 1 0 1 0 0 0 1 1 1 0 0 0 1 1 0 0 1 0 0 1 1 0 0 0 1 1 1 0 0 0 1 0 1 0 0 1 0 1 1 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 1 0 1 0 0 0 1 0 0 1 0 0 1 1 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1 1 1 0 1 0 0 1 1 0 0 0 1 1 0 1 0 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 0 0 1 0 0 1 1 0 0 0 1 1 0 1 0 0 0 1 1 1 0 0 0 0 1 0 0 0 1 1 1 0 1 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 1 0 1 0 0 1 0 0 1 0 0 0 1 0 1 0 0 1 0 0 1 0 0 1 1 0 0 1 0 1 0 0 0 0 1 1 1 0 1 0 0 0 1 1 0 0 0 1 0 1 0 0 0 1 0 0 1 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 1 0 0 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 0 0 0 1 1 0 1 0 0 0 1 0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0 1 1 1 0 0 0 1 1 0 1 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0 0 1 0 1 0 0 0 1 1 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 0 0 1 0 1 0 0 0 1 1 1 1 0 0 0 0 1 0 1 0 0 1 1 0 0 0 1 0 0 0 0 0 1 1 1 0 0 0 1 1 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 1 1 1 0 0 0 1 1 1 1 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 0 1 0 0 0 1 1 0 0 0 1 0 1 0 0 0 1 1 1 0 1 0 0 1 1 0 1 0 0 0 1 0 0 0 1 1 1 0 1 0 0 1 1 1 0 0 0 1 1 0 0 0 1 1 1 1 0 0 0 1 1 0 0 0 1 1 1 0 1 0 0 1 0 1 0 0 0 end label values firstgen firstgencategory label def firstgencategory 0 "Non-first-gen", modify label def firstgencategory 1 "First-gen", modify label values everenrollcollege everattendcategory label def everattendcategory 0 "0.No", modify label def everattendcategory 1 "1.Yes", modify
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