Identification of influential observation in linear structural relationship model with known slope

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

AMS SUBJECT CLASSIFICATION:

• 62H11

Acknowledgement

The authors are thankful to the referees and the editor of the journal for their very helpful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

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