Correlation curve estimation for multiplicative distortion measurement errors data

ABSTRACT

A correlation curve measures the strength of the association between two variables locally at different values of covariate. This paper studies how to estimate the correlation curve under the multiplicative distortion measurement errors setting. The unobservable variables are both distorted in a multiplicative fashion by an observed confounding variable. We obtain asymptotic normality results for the estimated correlation curve. We conduct Monte Carlo simulation experiments to examine the performance of the proposed estimator. The estimated correlation curve is applied to analyze a real dataset for an illustration.

KEYWORDS:

• Confounding variable
• errors-in-variables
• correlation curve
• kernel smoothing

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Jun Zhang  http://orcid.org/0000-0003-4332-5182

Additional information

Funding

Zhenghui Feng's research is supported by the Natural Science Foundation of Fujian Province of China, Grant No. 2017J01006; the Humanities and Social Sciences Foundation of Ministry of Education of China, 18YJC910006