Estimating a correlation coefficient when one variable is not directly observed

Lawrence S. Mayer

doi:10.1080/01621459.1973.10482446

Estimating a correlation coefficient when one variable is not directly observed

Lawrence S. Mayer

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

The problem is to estimate p the true correlation between two variables x and y when y and u=f(x) (but not x) are measured where f is a monotone function. The monotone correlation coefficient between y and u is defined and shown to be a (strongly) consistent estimator of p. For large samples approximate lower and upper bounds on the sample correlation between x and y are presented. Finally, an application of these results is displayed.

Original language	English (US)
Pages (from-to)	420-421
Number of pages	2
Journal	Journal of the American Statistical Association
Volume	68
Issue number	342
DOIs	https://doi.org/10.1080/01621459.1973.10482446
State	Published - Jun 1973
Externally published	Yes

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

Access to Document

10.1080/01621459.1973.10482446

Cite this

@article{c58897ab76fe46cba6aa2c93d6b3f0ad,

title = "Estimating a correlation coefficient when one variable is not directly observed",

abstract = "The problem is to estimate p the true correlation between two variables x and y when y and u=f(x) (but not x) are measured where f is a monotone function. The monotone correlation coefficient between y and u is defined and shown to be a (strongly) consistent estimator of p. For large samples approximate lower and upper bounds on the sample correlation between x and y are presented. Finally, an application of these results is displayed.",

author = "Mayer, \{Lawrence S.\}",

note = "Funding Information: • Lawrence S. Mayer is .....iatant professor, Department of Statistics, Virginia Polytechnic Institute and State Univeraity, Blacksburg, Virginia 24061. The reeeareh waa partia.lly 8UppOrted by the N{"}tional Institute of Mental Health under Grant No. NIH 1 R03 MH 21454 01. The author is indebted to an associate editor and referee for their excellent comments.",

year = "1973",

month = jun,

doi = "10.1080/01621459.1973.10482446",

language = "English (US)",

volume = "68",

pages = "420--421",

journal = "Journal of the American Statistical Association",

issn = "0162-1459",

publisher = "Taylor and Francis Ltd.",

number = "342",

}

TY - JOUR

T1 - Estimating a correlation coefficient when one variable is not directly observed

AU - Mayer, Lawrence S.

N1 - Funding Information: • Lawrence S. Mayer is .....iatant professor, Department of Statistics, Virginia Polytechnic Institute and State Univeraity, Blacksburg, Virginia 24061. The reeeareh waa partia.lly 8UppOrted by the N"tional Institute of Mental Health under Grant No. NIH 1 R03 MH 21454 01. The author is indebted to an associate editor and referee for their excellent comments.

PY - 1973/6

Y1 - 1973/6

N2 - The problem is to estimate p the true correlation between two variables x and y when y and u=f(x) (but not x) are measured where f is a monotone function. The monotone correlation coefficient between y and u is defined and shown to be a (strongly) consistent estimator of p. For large samples approximate lower and upper bounds on the sample correlation between x and y are presented. Finally, an application of these results is displayed.

AB - The problem is to estimate p the true correlation between two variables x and y when y and u=f(x) (but not x) are measured where f is a monotone function. The monotone correlation coefficient between y and u is defined and shown to be a (strongly) consistent estimator of p. For large samples approximate lower and upper bounds on the sample correlation between x and y are presented. Finally, an application of these results is displayed.

UR - https://www.scopus.com/pages/publications/33846229943

UR - https://www.scopus.com/pages/publications/33846229943#tab=citedBy

U2 - 10.1080/01621459.1973.10482446

DO - 10.1080/01621459.1973.10482446

M3 - Article

AN - SCOPUS:33846229943

SN - 0162-1459

VL - 68

SP - 420

EP - 421

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

IS - 342

ER -

Estimating a correlation coefficient when one variable is not directly observed

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this