Abstract:
In many applications of conditional logit models the choice set and the characteristics of that set are identical for groups of decision makers. In that case it is possible to obtain a more computationally efficient estimation of the model by grouping the data and employing "multin". The command "multin" is designed for estimation of grouped conditional logit models. It produces the same output as "clogit" but requires a more compact data layout. This is particularly relevant when the model comprises many observations and/or choices. In this situation it is possible to obtain substantial reductions in the size of the data set and the time required for estimation. The command "groupdata" converts the data as required by "clogit" to the new format required by "multin". The command "dirmul" performs Dirichlet-Multinomial (DM) regression which is a parametric alternative to deal with overdispersion in the context of the grouped conditional logit model. The "dirmul" command can also be used to estimate Beta-Binomial regression models.
Language: Stata Requires: Stata version 9 Keywords:conditional logit; grouped data; dirichlet-multinomial; Beta-Binomial (search for similar items in EconPapers) Date: 2007-01-19 Note: This module may be installed from within Stata by typing "ssc install groupcl". Windows users should not attempt to download these files with a web browser.
More software in Statistical Software Components from Boston College Department of Economics Address: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA Contact information at EDIRC. Series data maintained by Christopher F Baum ().
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