Skip to main content
Cross Validated

Return to Answer

added 4 characters in body
Source Link
Richard Hardy
Richard Hardy
  • 69.5k
  • 13
  • 126
  • 278

gmacfarlane has been very clear. But to be more precise, and I assume you perform a cross section analysis, the core assumption is the IIA (independence of irrelevant alternatives). 
You can not force your data fit into the IIA assumption, you should test it and hope for it to be satisfied. SpssSPSS could not handle the test until 2010 for sure. R of course does it, but it might me easier for you to migrate to stataStata and implement the IIA tests provided by the mlogitmlogit postestimation commands.

If the IIA does not holds, mixed multinomial logit or nested logit are reasonable alternatives. The first one can be estimated within the gllammgllamm, the second with the far more parsimonious nlogitnlogit command.

gmacfarlane has been very clear. But to be more precise, and I assume you perform a cross section analysis, the core assumption is the IIA (independence of irrelevant alternatives). You can not force your data fit into the IIA assumption, you should test it and hope for it to be satisfied. Spss could not handle the test until 2010 for sure. R of course does it, but it might me easier for you to migrate to stata and implement the IIA tests provided by the mlogit postestimation commands.

If the IIA does not holds, mixed multinomial logit or nested logit are reasonable alternatives. The first one can be estimated within the gllamm, the second with the far more parsimonious nlogit command.

gmacfarlane has been very clear. But to be more precise, and I assume you perform a cross section analysis, the core assumption is the IIA (independence of irrelevant alternatives). 
You can not force your data fit into the IIA assumption, you should test it and hope for it to be satisfied. SPSS could not handle the test until 2010 for sure. R of course does it, but it might me easier for you to migrate to Stata and implement the IIA tests provided by the mlogit postestimation commands.

If the IIA does not holds, mixed multinomial logit or nested logit are reasonable alternatives. The first one can be estimated within the gllamm, the second with the far more parsimonious nlogit command.

Source Link
JDav
JDav
  • 771
  • 4
  • 8

gmacfarlane has been very clear. But to be more precise, and I assume you perform a cross section analysis, the core assumption is the IIA (independence of irrelevant alternatives). You can not force your data fit into the IIA assumption, you should test it and hope for it to be satisfied. Spss could not handle the test until 2010 for sure. R of course does it, but it might me easier for you to migrate to stata and implement the IIA tests provided by the mlogit postestimation commands.

If the IIA does not holds, mixed multinomial logit or nested logit are reasonable alternatives. The first one can be estimated within the gllamm, the second with the far more parsimonious nlogit command.