Is NLOGIT 6 good for all types of logistic models, like Multinomial Logit model, Mixed Logit mode, Conditional Logit model, nested Logit model, and others?
and what is it cons?
Hi!
NLOGIT is great for discrete choice modelling. You can estimate all of the models you have enumerated. The advantage in my opinion is that it is relatively easy to estimate a model, at it is quite flexible (for example allowing choice sets to vary across choice occasions). There are a few very well-written books that use NLOGIT examples.
However, it presents some disadvantages. First, it is an expensive software. Second, for example, if you specify a mixed logit model, the maximum number of parameters that can be random is 25. Moreover, there is a limit to how many observations you can have per dataset (it was quite a high limit, but my dataset was longer than allowed). Also, since there are fewer users, the online help forums are less active.
Cheers,
Ana
Ana Faria Lopes thank you for the valuable answer
Do you recommend me to use Stata 16 instead?
Dear Jamil
Nlogit contain a large array of tools for data analysis, data management and containsmodel building from simple linear regression to maximum likelihood estimation of nonlinear systems of equations, with many extensions and the variations. Nearly all techniques used in modern empirical investigation containsare provided.
It is a very good sofware in discrete choice modelling but it is expensive (about 1000 $).
Python Biogeme is another valuable alternative.modeling software.
The following linke compare discrete choice modelling softwares:
https://wiki.ece.cmu.edu/ddl/index.php/Software_for_discrete_choice_model_estimation
hope to be useful.
Cordially,
Hossein
Mohammadhossein Abbasi In Python Biogeme and RStudio, the data shaping is time consuming and not easy, I prefer using interface packages to avoid wasting my time with code.
Thanks for information , much appreciated
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