Estimating the reliability of an exposure variable in the presence of confounders

Mimi Kim, B. S. Pasternack, R. J. Carroll, K. L. Koenig, P. G. Toniolo

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this paper we discuss estimation of the reliability of an exposure variable in the presence of confounders measured without error. We give an explicit formula that shows how the exposure becomes less reliable as the degree of correlation between the exposure and confounders increases. We also discuss biases in the corresponding logistic regression estimates and methods for correction. Data from a matched case-control study of hormone levels and risk of breast cancer are used to illustrate the methods.

Original languageEnglish (US)
Pages (from-to)1437-1446
Number of pages10
JournalStatistics in Medicine
Volume14
Issue number13
StatePublished - 1995
Externally publishedYes

Fingerprint

Matched Case-control Study
Case-Control Studies
Regression Estimate
Logistic Models
Hormones
Breast Neoplasms
Logistic Regression
Breast Cancer
Explicit Formula

ASJC Scopus subject areas

  • Epidemiology

Cite this

Kim, M., Pasternack, B. S., Carroll, R. J., Koenig, K. L., & Toniolo, P. G. (1995). Estimating the reliability of an exposure variable in the presence of confounders. Statistics in Medicine, 14(13), 1437-1446.

Estimating the reliability of an exposure variable in the presence of confounders. / Kim, Mimi; Pasternack, B. S.; Carroll, R. J.; Koenig, K. L.; Toniolo, P. G.

In: Statistics in Medicine, Vol. 14, No. 13, 1995, p. 1437-1446.

Research output: Contribution to journalArticle

Kim, M, Pasternack, BS, Carroll, RJ, Koenig, KL & Toniolo, PG 1995, 'Estimating the reliability of an exposure variable in the presence of confounders', Statistics in Medicine, vol. 14, no. 13, pp. 1437-1446.
Kim M, Pasternack BS, Carroll RJ, Koenig KL, Toniolo PG. Estimating the reliability of an exposure variable in the presence of confounders. Statistics in Medicine. 1995;14(13):1437-1446.
Kim, Mimi ; Pasternack, B. S. ; Carroll, R. J. ; Koenig, K. L. ; Toniolo, P. G. / Estimating the reliability of an exposure variable in the presence of confounders. In: Statistics in Medicine. 1995 ; Vol. 14, No. 13. pp. 1437-1446.
@article{ae1071bd38664a5f9f1b114ca0812ebd,
title = "Estimating the reliability of an exposure variable in the presence of confounders",
abstract = "In this paper we discuss estimation of the reliability of an exposure variable in the presence of confounders measured without error. We give an explicit formula that shows how the exposure becomes less reliable as the degree of correlation between the exposure and confounders increases. We also discuss biases in the corresponding logistic regression estimates and methods for correction. Data from a matched case-control study of hormone levels and risk of breast cancer are used to illustrate the methods.",
author = "Mimi Kim and Pasternack, {B. S.} and Carroll, {R. J.} and Koenig, {K. L.} and Toniolo, {P. G.}",
year = "1995",
language = "English (US)",
volume = "14",
pages = "1437--1446",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "John Wiley and Sons Ltd",
number = "13",

}

TY - JOUR

T1 - Estimating the reliability of an exposure variable in the presence of confounders

AU - Kim, Mimi

AU - Pasternack, B. S.

AU - Carroll, R. J.

AU - Koenig, K. L.

AU - Toniolo, P. G.

PY - 1995

Y1 - 1995

N2 - In this paper we discuss estimation of the reliability of an exposure variable in the presence of confounders measured without error. We give an explicit formula that shows how the exposure becomes less reliable as the degree of correlation between the exposure and confounders increases. We also discuss biases in the corresponding logistic regression estimates and methods for correction. Data from a matched case-control study of hormone levels and risk of breast cancer are used to illustrate the methods.

AB - In this paper we discuss estimation of the reliability of an exposure variable in the presence of confounders measured without error. We give an explicit formula that shows how the exposure becomes less reliable as the degree of correlation between the exposure and confounders increases. We also discuss biases in the corresponding logistic regression estimates and methods for correction. Data from a matched case-control study of hormone levels and risk of breast cancer are used to illustrate the methods.

UR - http://www.scopus.com/inward/record.url?scp=0029053778&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029053778&partnerID=8YFLogxK

M3 - Article

VL - 14

SP - 1437

EP - 1446

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 0277-6715

IS - 13

ER -