A new confidence interval in errors-in-variables model with known error variance

Liang Yan, Rui Wang and Xingzhong Xu

Journal of Applied Statistics, 2017, vol. 44, issue 12, 2204-2221

Abstract: This paper considers constructing a new confidence interval for the slope parameter in the structural errors-in-variables model with known error variance associated with the regressors. Existing confidence intervals are so severely affected by Gleser–Hwang effect that they are subject to have poor empirical coverage probabilities and unsatisfactory lengths. Moreover, these problems get worse with decreasing reliability ratio which also result in more frequent absence of some existing intervals. To ease these issues, this paper presents a fiducial generalized confidence interval which maintains the correct asymptotic coverage. Simulation results show that this fiducial interval is slightly conservative while often having average length comparable or shorter than the other methods. Finally, we illustrate these confidence intervals with two real data examples, and in the second example some existing intervals do not exist.

Date: 2017
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DOI: 10.1080/02664763.2016.1247793

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