Estimation of the Correlation Coefficient for a Bivariate Normal Distribution with Missing Data

Authors

  • Juthaphorn Sinsomboonthong Department of Statistics, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.

Keywords:

bivariate normal distribution, correlation coefficient, bias, missing data, mean square error

Abstract

This study proposes an estimator of the correlation coefficient for a bivariate normal distribution with missing data, via the complete observation analysis method. Evaluation of the proposed estimator (ˆρ J) in comparison with the Pearson correlation coefficient (ˆρP ) was conducted using a simulation study. It was found that, for a higher percentage of missing data in a large sample size, the absolute bias of ˆρ J was less than that of ˆρ P when the population correlation coefficients (ρ) were not close to zero. In addition, the mean square error of ˆρJ was not different from that of ˆρP in each situation.

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Published

2011-08-30

How to Cite

Juthaphorn Sinsomboonthong. 2011. “Estimation of the Correlation Coefficient for a Bivariate Normal Distribution With Missing Data”. Agriculture and Natural Resources 45 (4). Bangkok, Thailand:736-42. https://li01.tci-thaijo.org/index.php/anres/article/view/245351.

Issue

Vol. 45 No. 4 (2011): July-August

Section

Research Article

License

online 2452-316X print 2468-1458/Copyright © 2022. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/),
production and hosting by Kasetsart University of Research and Development Institute on behalf of Kasetsart University.