The correlation coefficient is widely used to quantify the degree of association between two quantitative variables. By resorting to the geometric representation of the linear correlation coefficient, it is possible to calculate the upper and lower bounds of the correlation coefficient between two variables Xl, x 2 when the correlation coefficients with a third variable x 3 are available. Implications in observational studies, where x3 could be a proxy of a target variable x2, whose direct measurement is too expensive or impractical, are discussed.

Admissibility intervals for linear correlation coefficients

Canal, Luisa;Micciolo, Rocco
2007-01-01

Abstract

The correlation coefficient is widely used to quantify the degree of association between two quantitative variables. By resorting to the geometric representation of the linear correlation coefficient, it is possible to calculate the upper and lower bounds of the correlation coefficient between two variables Xl, x 2 when the correlation coefficients with a third variable x 3 are available. Implications in observational studies, where x3 could be a proxy of a target variable x2, whose direct measurement is too expensive or impractical, are discussed.
2007
2
Canal, Luisa; Micciolo, Rocco
File in questo prodotto:
File Dimensione Formato  
2007-Canal-SP.pdf

accesso aperto

Tipologia: Post-print referato (Refereed author’s manuscript)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 257.58 kB
Formato Adobe PDF
257.58 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/69702
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
  • OpenAlex ND
social impact