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

Mimi Y. Kim; Bernard S. Pasternack; Raymond J. Carroll; Karen L. Koenig; Paolo G. Toniolo

doi:10.1002/sim.4780141304

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

Mimi Y. Kim, Bernard S. Pasternack, Raymond J. Carroll, Karen L. Koenig, Paolo G. Toniolo

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

2 Scopus citations

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 language	English (US)
Pages (from-to)	1437-1446
Number of pages	10
Journal	Statistics in Medicine
Volume	14
Issue number	13
DOIs	https://doi.org/10.1002/sim.4780141304
State	Published - Jul 15 1995
Externally published	Yes

ASJC Scopus subject areas

Epidemiology
Statistics and Probability

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/sim.4780141304

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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 = "Kim, {Mimi Y.} and Pasternack, {Bernard S.} and Carroll, {Raymond J.} and Koenig, {Karen L.} and Toniolo, {Paolo G.}",

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AU - Kim, Mimi Y.

AU - Pasternack, Bernard S.

AU - Carroll, Raymond J.

AU - Koenig, Karen L.

AU - Toniolo, Paolo G.

PY - 1995/7/15

Y1 - 1995/7/15

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.

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

Abstract

ASJC Scopus subject areas

UN SDGs

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