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st: Updated version of -gologit2- now available


From   Richard Williams <Richard.A.Williams.5@ND.edu>
To   statalist@hsphsun2.harvard.edu
Subject   st: Updated version of -gologit2- now available
Date   Mon, 01 Aug 2005 11:21:24 -0500

Thanks to Kit Baum, version 2.01 of -gologit2- is now available from SSC. The new release features several bug fixes, a test of the autofitted model that was suggested by Kit Baum, and improved documentation. In addition, there is now a -gologit2- web page that goes over the theory behind -gologit2- and provides detailed examples of its use: see

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

-gologit2- is a user-written program that estimates generalized logistic regression 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. -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 two special cases of the generalized model: the proportional odds model and the partial proportional odds model. (It can also estimate a third special case, 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, while the pl (parallel lines) and npl (non-parallel lines) options can be used when users wish to specify the model themselves.

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), Stata 8.2 survey data (svy) estimation, and the computation of estimated probabilities via the -predict- command.

To install -gologit2-: From within Stata, type

findit gologit2


-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
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HOME: (574)289-5227
EMAIL: Richard.A.Williams.5@ND.Edu
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