R2O: Stata module to calculate an ordinal explained variation statistic

Mike Lacy ()
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Mike Lacy: Colorado State University

Statistical Software Components from Boston College Department of Economics

Abstract: r2o calculates the ordinal explained variation statistic (i.e., R-squared) described by Lacy (2006), which is used to summarize the fit of a regression model for an ordinal response. It rests on an ordinal variation measure that entails no assumptions about intercategory distances or distributional form. This measure is valid regardless of the method used to estimate the model, and was shown to outperform various pseudo-R-squared measures in estimating the value of the true R-squared for a regression model for an underlying continuous response, even though its sense does not require such. -r2o- is to be used after a relevant categorical response model has been run, while the e() list is still intact. By default, the program recognizes the following as relevant response models: -ologit-, -oprobit-, -mlogit-, and -gologit2-. However, -r2o- should work after any estimation command for which –predict- p1,..., pk will calculate predicted probabilities, and which follows official Stata's conventions for naming items in the e() list.

Language: Stata
Requires: Stata version 7
Keywords: ordinal explained variation; R-squared; goodness of fit (search for similar items in EconPapers)
Date: 2010-10-14
Note: This module should be installed from within Stata by typing "ssc install r2o". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/r/r2o.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/r/r2o.hlp help file (text/plain)

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Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s457189

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