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st: gologit2 2.1.4 now available from SSC


From   Richard Williams <Richard.A.Williams.5@ND.edu>
To   statalist@hsphsun2.harvard.edu
Subject   st: gologit2 2.1.4 now available from SSC
Date   Fri, 02 Feb 2007 22:53:07 -0500

Thanks to Kit Baum, an updated version of -gologit2- is now available from SSC. The old version computed Pseudo R^2 incorrectly when pweights were used. This problem and others have been fixed and there have also been minor improvements in the documentation.

gologit2 is a user-written program that estimates generalized ordered logit models for ordinal dependent variables. The actual values taken on by the dependent variable are irrelevant except that larger values are assumed to correspond to "higher" outcomes. Up to 20 outcomes are allowed. gologit2 is inspired by Vincent Fu's gologit program and is backward compatible with it but offers several additional powerful options.

A major strength of gologit2 is that it can also estimate three special cases of the generalized model: the proportional odds/parallel lines model, the partial proportional odds model, and the logistic regression model. Hence, gologit2 can estimate models that are less restrictive than the proportional odds /parallel lines models estimated by ologit (whose assumptions are often violated) but more parsimonious and interpretable than those estimated by a non-ordinal method, such as multinomial logistic regression (i.e. mlogit). The autofit option greatly simplifies the process of identifying partial proportional odds models that fit the data.

An alternative but equivalent parameterization of the model that has appeared in the literature is reported when the gamma option is selected. Other key advantages of gologit2 include support for linear constraints (making it possible to use gologit2 for constrained logistic regression), survey data estimation, and the computation of estimated probabilities via the predict command.

Also, if the user considers them more appropriate for their data, probit, complementary log-log, log-log and cauchit links can be used instead of logit by specifying the link option, e.g. link(l) for logit (the default), link(p) for probit, link(c) for complementary log-log, link(ll) for log-log, and link(ca) for cauchit.

gologit2 works under both Stata 8.2 and Stata 9 or higher. Syntax is the same for both versions; but if you are using Stata 9 or higher, gologit2 supports several prefix commands, including by, nestreg, xi and sw. Stata 9's svy prefix command is NOT currently supported; use the svy option instead.

If you want to estimate marginal effects after gologit2, it is recommended that you install the most current versions of the user-written mfx2 and/or margeff commands, both available from SSC. These commands are generally easier to use than mfx and make it possible to output the results using table-formatting programs like outreg2 and estout.

More information on the statistical theory behind gologit2 as well as several worked examples and a troubleshooting FAQ can be found at

http://www.nd.edu/~rwilliam/gologit2/.



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Richard Williams, Notre Dame Dept of Sociology
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