st: gologit2 version 2.1.0

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

Thanks to Kit Baum, yet another update to -gologit2- is now available 
from SSC - and unlike most previous updates, this one actually offers 
some added functionality and not just bug fixes!

* While gologit2 continues to work in Stata 8.2, if you are using 
Stata 9, the by, nestreg, stepwise, xi, and possibly other prefix 
commands are allowed.  That is, Stata 9 users get added functionality 
but everything else still works ok if you have 8.2.  (I'm not sure 
how much longer I will try to keep new versions running under 8.2 but 
for now at least it was surprisingly easy to do.)

* If the user considers them more appropriate for their data, probit, 
complementary log-log, and log-log links can be used instead of 
logit. The link() function specifies the link function to be 
used.  The legal values are link(logit), link(probit), link(cloglog) 
and link(loglog) which can abbreviated as link(l), link(p), link(c) 
and link(ll). link(logit) is the default if the option is omitted.

* The ancillary file gologit2.pdf contains many examples and has been 
updated to document the new features.  However, ancillary files do 
not automatically get updated when you update the program.  Therefore 
you may wish to download it directly from

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

* For more info, there is a gologit2 general info page at

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

and a troubleshooting FAQ at

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

Here is the overall description of the program:

gologit2 estimates generalized ordered logit models for ordinal 
dependent variables. 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). Other key
strengths of gologit2 include options for linear constraints, 
alternative model parameterizations, automated model fitting, survey 
data (svy) estimation, alternative link functions (logit, probit, 
complementary log-log and log-log), and the computation of estimated 
probabilities via the predict command. 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. gologit2 is inspired by Vincent Fu's gologit program and 
is backward compatible with it but offers several additional powerful options.

-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
FAX:    (574)288-4373
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
WWW (personal):    http://www.nd.edu/~rwilliam
WWW (department):    http://www.nd.edu/~soc  
*
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