The consultant's forum. Reader reaction. Algorithms versus models for analyzing data that contain misclassification errors

A. Ekholm, M. A. Espeland, Siu Hui

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Espeland and Hui (1987, Biometrics 43, 1001-1012) propose a methodology for analysing epidemiologic data contaminated by misclassification. They explicate their algorithm by a data set concerning cervical cancer and circumcision. We reanalyse these data using a conditional independence assumption different from theirs, and reach radically different conclusions. Espeland and Hui's methodology is a form of correlation analysis. We propose an alternative methodology based on the logic of regression analysis.

Original languageEnglish (US)
Pages (from-to)1171-1182
Number of pages12
JournalBiometrics
Volume47
Issue number3
StatePublished - 1991
Externally publishedYes

Fingerprint

Misclassification Error
consultants
Biometrics
Consultants
Regression analysis
Uterine Cervical Neoplasms
Regression Analysis
Methodology
uterine cervical neoplasms
Conditional Independence
Misclassification
Correlation Analysis
biometry
Cancer
regression analysis
methodology
Model
Logic
Alternatives
Datasets

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Public Health, Environmental and Occupational Health
  • Agricultural and Biological Sciences (miscellaneous)
  • Applied Mathematics
  • Statistics and Probability

Cite this

The consultant's forum. Reader reaction. Algorithms versus models for analyzing data that contain misclassification errors. / Ekholm, A.; Espeland, M. A.; Hui, Siu.

In: Biometrics, Vol. 47, No. 3, 1991, p. 1171-1182.

Research output: Contribution to journalArticle

@article{d5b03efddc8b40bdb7fb38a8f2b92a41,
title = "The consultant's forum. Reader reaction. Algorithms versus models for analyzing data that contain misclassification errors",
abstract = "Espeland and Hui (1987, Biometrics 43, 1001-1012) propose a methodology for analysing epidemiologic data contaminated by misclassification. They explicate their algorithm by a data set concerning cervical cancer and circumcision. We reanalyse these data using a conditional independence assumption different from theirs, and reach radically different conclusions. Espeland and Hui's methodology is a form of correlation analysis. We propose an alternative methodology based on the logic of regression analysis.",
author = "A. Ekholm and Espeland, {M. A.} and Siu Hui",
year = "1991",
language = "English (US)",
volume = "47",
pages = "1171--1182",
journal = "Biometrics",
issn = "0006-341X",
publisher = "Wiley-Blackwell",
number = "3",

}

TY - JOUR

T1 - The consultant's forum. Reader reaction. Algorithms versus models for analyzing data that contain misclassification errors

AU - Ekholm, A.

AU - Espeland, M. A.

AU - Hui, Siu

PY - 1991

Y1 - 1991

N2 - Espeland and Hui (1987, Biometrics 43, 1001-1012) propose a methodology for analysing epidemiologic data contaminated by misclassification. They explicate their algorithm by a data set concerning cervical cancer and circumcision. We reanalyse these data using a conditional independence assumption different from theirs, and reach radically different conclusions. Espeland and Hui's methodology is a form of correlation analysis. We propose an alternative methodology based on the logic of regression analysis.

AB - Espeland and Hui (1987, Biometrics 43, 1001-1012) propose a methodology for analysing epidemiologic data contaminated by misclassification. They explicate their algorithm by a data set concerning cervical cancer and circumcision. We reanalyse these data using a conditional independence assumption different from theirs, and reach radically different conclusions. Espeland and Hui's methodology is a form of correlation analysis. We propose an alternative methodology based on the logic of regression analysis.

UR - http://www.scopus.com/inward/record.url?scp=0026218433&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0026218433&partnerID=8YFLogxK

M3 - Article

C2 - 1742437

AN - SCOPUS:0026218433

VL - 47

SP - 1171

EP - 1182

JO - Biometrics

JF - Biometrics

SN - 0006-341X

IS - 3

ER -