Influential data cases when the Cp criterion is used for variable selection in multiple linear regression

Authors:
S. J. Steel;D. W. Uys
Affiliations:
Department of Statistics and Actuarial Science, Stellenbosch University, Private Bag X1, 7602 Matieland, South Africa;Department of Statistics and Actuarial Science, Stellenbosch University, Private Bag X1, 7602 Matieland, South Africa
Venue:
Computational Statistics & Data Analysis
Year:
2006

Citing 3
Cited 0

Impact of simultaneous omission of a variable and an observation on a linear regression equation

Computational Statistics & Data Analysis
More comments on Cp

Technometrics
A method for simultaneous variable selection and outlier identification in linear regression

Computational Statistics & Data Analysis

Quantified Score

Hi-index	0.03

Visualization

Abstract

The influence of data cases when the C"p criterion is used for variable selection in multiple linear regression analysis is studied in terms of the predictive power and the predictor variables included in the resulting model when variable selection is applied. In particular, the focus is on the importance of identifying and dealing with these so-called selection influential data cases before model selection and fitting are performed. A new selection influence measure based on the C"p criterion to identify selection influential data cases is developed. The success with which this influence measure identifies selection influential data cases is evaluated in two example data sets.