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st: New version of oglm and oglm9 now available


From   Richard Williams <richardwilliams.ndu@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: New version of oglm and oglm9 now available
Date   Fri, 11 Feb 2011 12:33:06 -0500

Thanks to Kit Baum, a new version of oglm is now available on SSC. The new version requires Stata 11.1 and works with factor variables and the margins command. Those with Stata 9 and 10 should use the old version of oglm, which has been renamed oglm9. Special thanks to Kerry Kammire, who played a major role in helping me get oglm updated for Stata 11.

oglm estimates Ordinal Generalized Linear Models. When these models include equations for heteroskedasticity they are also known as heterogeneous choice/ location-scale / heteroskedastic ordinal regression models. oglm supports multiple link functions, including logit (the default), probit, complementary log-log, log-log and cauchit. SPSS's PLUM routine helped to inspire oglm and provided a means for double-checking the accuracy of the program.

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. Heterogeneous choice/ location-scale models explicitly specify the determinants of heteroskedasticity in an attempt to correct for it. Further, these models can be used when the variance/variability of underlying attitudes is itself of substantive interest. Alvarez and Brehm (1995), for example, argued that individuals whose core values are in conflict will have a harder time making a decision about abortion and will hence have greater variability/error variances in their responses.

"Fitting Heterogeneous Choice Models with oglm" appears in the most recent issue of The Stata Journal. Besides showing how to use the program, the paper shows how Allison's (1999) model for comparing logit and probit coefficients across groups, and Hauser and Andrew's (2006) Logistic Response Model with Proportionality Constraints (LRPC), are special cases or reparameterizations of the heterogeneous choice model and can be estimated with oglm.

For more on oglm, see

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


References:

Allison, P. D. 1999. Comparing logit and probit coefficients across groups. Sociological Methods and Research 28: 186-208.

Hauser, R. M., and M. Andrew. 2006. Another look at the stratification of educational transitions: The logistic response model with partial proportionality constraints. Sociological Methodology 36: 1-26.

Williams, Richard. 2009. Using heterogenous choice models to compare logit and probit coefficients across groups. Sociological Methods & Research 37: 531-559.

Williams, Richard. 2010. "Fitting Heterogeneous Choice Models with oglm." The Stata Journal 10(4):540-567.

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Richard Williams, Notre Dame Dept of Sociology
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EMAIL:  Richard.A.Williams.5@ND.Edu
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