English, Article edition: PERTURB: Stata module to evaluate collinearity and ill-conditioning John Hendrickx

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Bookmark: http://trove.nla.gov.au/version/103068
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  • code
Language
  • English

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Title
  • PERTURB: Stata module to evaluate collinearity and ill-conditioning
Author
  • John Hendrickx
Physical Description
  • code
Notes
  • 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.
  • collinearity, conditioning
  • RePEc:boc:bocode:s445201
Language
  • English
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