Estimation of the Correlation Coefficient Based on Selected Data

Gösta Hägglund and Rolf Larsson

Journal of Educational and Behavioral Statistics, 2006, vol. 31, issue 4, 377-411

Abstract: In psychometrics, it is often the case that one encounters data that may not be considered random but selected in a systematic way according to some explanatory variable. In this article, maximum likelihood estimation is considered when data are supposed to arise from a bivariate normal distribution that is truncated in an extreme way. Two methods are presented and compared, one of them being purely numerical, while the other is based on an approximation. Both methods are tried on both simulated and on real data. The purely numerical method is shown to be the most reliable over all, but in some cases, the computationally less burdensome approximate method turns out to work almost as well.

Keywords: correlation coefficient; maximum likelihood; selected data (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986031004377 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:31:y:2006:i:4:p:377-411

DOI: 10.3102/10769986031004377

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().