Identification of influential observation in linear structural relationship model with known slope
Document Type
Article
Publication Date
1-2-2022
Abstract
A number of identification techniques are available in the literature to detect influential observations in linear regression models. However, the issue of the identification of influential observations in errors-in-variable models is still not very explored. In this paper we propose a new method for the identification of influential observations based on the COVRATIO statistic when the slope parameter is known. We determine the cut off point for this model on the basis of Monte Carlo simulation study and show that this cut off point performs well in the identification of influential observation in linear structural relationship model with known slope parameter. Finally, we present a real world example which also supports the findings obtained by the simulations earlier.
Keywords
Influential observations, Errors-in-variable model, COVRATIO statistic, Power of performance
Divisions
mathematics
Publication Title
Communications in Statistics - Simulation and Computation
Volume
51
Issue
1
Publisher
Taylor & Francis
Publisher Location
530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA