How Robust is Linear Regression with Dummy Variables ?

dc.contributor.author	Blankmeyer, Eric
dc.date.accessioned	2006-11-03T10:21:54Z
dc.date.available	2012-02-24T10:21:54Z
dc.date.issued	2006-11
dc.description.abstract	Researchers in education and the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of which may contain only a few observations. Such groups may easily contain enough outliers to break down the parameter estimates. Models with many fixed or random effects appear to be especially vulnerable to outlying data. This paper discusses the problem at an intuitive level and cites sources for the key theorems establishing bounds on the breakdown point in models with dummy variables.
dc.description.department	Finance and Economics
dc.format	Text
dc.format.extent	14 pages
dc.format.medium	1 file (.pdf)
dc.identifier.citation	Blankmeyer, E. (2006). How robust is linear regression with dummy variables? Texas State University-San Marcos, San Marcos, Texas.
dc.identifier.uri	https://hdl.handle.net/10877/4105
dc.language.iso	en
dc.publisher	Texas State University-San Marcos
dc.subject	breakdown point
dc.subject	outliers
dc.subject	fixed effects
dc.title	How Robust is Linear Regression with Dummy Variables ?
dc.type	Paper

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