PERTURB: Stata module to evaluate collinearity and ill-conditioning

John Hendrickx

Statistical Software Components from Boston College Department of Economics

Abstract: perturb is a tool for assessing the impact of small random changes (perturbations) to variables on parameter estimates. It is an alternative for collinearity diagnostics such as vif, collin, coldiag, coldiag2. perturb is particularly useful for evaluating collinearity if interactions are present or nonlinear transformations of variables, e.g. a squared term. peturb can show how the perturbations affect the estimates of a variable and terms derived from it whereas other collinearity diagnostics simply treat interactions and transformations as regular independent variables. perturb is not limited to linear regression but can be used for all regression-like models. perturb can also deal with categorical variables by randomly misclassifying them to assess the impact on parameter estimates.

Language: Stata
Requires: Stata version 7.0
Keywords: collinearity; conditioning (search for similar items in EconPapers)
Date: 2004-08-16, Revised 2004-12-09
Note: This module should be installed from within Stata by typing "ssc install perturb". 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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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/p/perturb.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/p/perturb.hlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/r/reclass.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/r/reclass.hlp help file (text/plain)

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