st: Updated version of -gologit2- now available

[Richard Williams <Richard.A.Williams.5@ND.edu>]

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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EMAIL:  Richard.A.Williams.5@ND.Edu
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WWW (department):    http://www.nd.edu/~soc

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