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GOLOGIT2: Stata module to estimate generalized logistic regression models for ordinal dependent variables

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  • Richard Williams

    ()
    (University of Notre Dame)

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    Abstract

    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, log-log & cauchit), 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. Also see Stata Journal, 6(1), 58-82.

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    File URL: http://fmwww.bc.edu/repec/bocode/g/gologit2.ado
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    File URL: http://www.nd.edu/~rwilliam/gologit2/
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    Bibliographic Info

    Software component provided by Boston College Department of Economics in its series Statistical Software Components with number S453401.

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    Programming language: Stata
    Requires: Stata version 8.2
    Date of creation: 14 Jun 2005
    Date of revision: 31 Jan 2013
    Handle: RePEc:boc:bocode:s453401

    Note: This module should be installed from within Stata by typing "ssc install gologit2". Windows users should not attempt to download these files with a web browser.
    Contact details of provider:
    Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA
    Phone: 617-552-3670
    Fax: +1-617-552-2308
    Email:
    Web page: http://fmwww.bc.edu/EC/
    More information through EDIRC

    Order Information:
    Web: http://repec.org/docs/ssc.php

    Related research

    Keywords: logistic; logistic regression; generalized logit; proportional odds; partial proportional odds; logit; probit; cloglog; loglog; cauchit;

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