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OGLM9: Stata module to estimate Ordinal Generalized Linear Models

Author

Listed:
  • Richard Williams

    () (University of Notre Dame)

Abstract

oglm estimates Ordinal Generalized Linear Models. It supports several link functions, including logit, probit, complementary log-log, log-log and cauchit. When an ordinal regression model incorrectly assumes that error variances are the same for all cases, the standard errors are wrong and (unlike OLS regression) the parameter estimates are biased. With oglm you can estimate heterogeneous choice/ location-scale models that explicitly specify the determinants of heteroskedasticity in an attempt to understand and correct for it. Several other special cases of ordinal generalized linear models can also be estimated by oglm. oglm was inspired by the SPSS PLUM routine but differs somewhat in its terminology, labeling of links, and the variables that are allowed when modeling heteroskedasticity. oglm9 is the last version of oglm that runs on Stata 9 & 10. Stata 11+ users should use oglm instead.

Suggested Citation

  • Richard Williams, 2011. "OGLM9: Stata module to estimate Ordinal Generalized Linear Models," Statistical Software Components S457244, Boston College Department of Economics.
  • Handle: RePEc:boc:bocode:s457244
    Note: This module should be installed from within Stata by typing "ssc install oglm9". Windows users should not attempt to download these files with a web browser.
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    File URL: http://fmwww.bc.edu/repec/bocode/o/oglm9.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/o/oglm9_ll.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/o/oglm9_p.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/o/oglm9.hlp
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    File URL: https://www.nd.edu/~rwilliam/oglm/
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