Derivation of Passing–Bablok regression from Kendall’s tau

Dufey Florian ()
Additional contact information
Dufey Florian: Roche Diagnostics GmbH Standort Penzberg, Biostatistics, DXREBA, Nonnenwald 2, Penzberg, 82377, Germany

The International Journal of Biostatistics, 2020, vol. 16, issue 2, 00

Abstract: It is shown how Passing’s and Bablok’s robust regression method may be derived from the condition that Kendall’s correlation coefficient tau shall vanish upon a scaling and rotation of the data. If the ratio of the standard deviations of the regressands is known, a similar procedure leads to a robust alternative to Deming regression, which is known as the circular median of the doubled slope angle in the field of directional statistics. The derivation of the regression estimates from Kendall’s correlation coefficient makes it possible to give analytical estimates of the variances of the slope, intercept, and of the bias at medical decision point, which have not been available to date. Furthermore, it is shown that using Knight’s algorithm for the calculation of Kendall’s tau makes it possible to calculate the Passing–Bablok estimator in quasi-linear time. This makes it possible to calculate this estimator rapidly even for very large data sets. Examples with data from clinical medicine are also provided.

Keywords: Kendall’s tau; method comparison; Passing–Bablok regression; robust regression; Theil–Sen regression (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/ijb-2019-0157 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:ijbist:v:16:y:2020:i:2:p:00:n:11

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/ijb/html

DOI: 10.1515/ijb-2019-0157

Access Statistics for this article

The International Journal of Biostatistics is currently edited by Antoine Chambaz, Alan E. Hubbard and Mark J. van der Laan

More articles in The International Journal of Biostatistics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().