Estimation of response probability in correlated binary data: A new approach

Sin ho Jung, Chul Ahn

Research output: Contribution to journalArticle

Abstract

We consider analysis of binary observations from multiple sites of each subject. In this case, observations from the same subject tend to be correlated. In estimating the common response probability in correlated binary data, two weighting systems have been most popular: equal weights to sites, and equal weights to subjects. When the number of sites varies subject by subject, performance of these two weighting systems depends on the extent of correlation among sites within each subject. In this paper, we describe a new weighting method that minimizes the variance of the estimator. We apply these methods to data from a study involving an enzymatic diagnostic test to illustrate the estimation of the sensitivity and the specificity of periodontal diagnostic tests. Simulation studies were conducted to compare the performance of the new estimator with that of other estimators.

Original languageEnglish (US)
Pages (from-to)599-604
Number of pages6
JournalTherapeutic Innovation & Regulatory Science
Volume34
Issue number2
DOIs
StatePublished - 2000

Fingerprint

Routine Diagnostic Tests
Weights and Measures
Sensitivity and Specificity

Keywords

  • Intraclass correlation
  • Optimal weight
  • Sensitivity
  • Specificity

ASJC Scopus subject areas

  • Pharmacology, Toxicology and Pharmaceutics (miscellaneous)
  • Public Health, Environmental and Occupational Health
  • Pharmacology (medical)

Cite this

Estimation of response probability in correlated binary data : A new approach. / Jung, Sin ho; Ahn, Chul.

In: Therapeutic Innovation & Regulatory Science, Vol. 34, No. 2, 2000, p. 599-604.

Research output: Contribution to journalArticle

@article{04a3a615e17b47e8ba2667c2f7573e65,
title = "Estimation of response probability in correlated binary data: A new approach",
abstract = "We consider analysis of binary observations from multiple sites of each subject. In this case, observations from the same subject tend to be correlated. In estimating the common response probability in correlated binary data, two weighting systems have been most popular: equal weights to sites, and equal weights to subjects. When the number of sites varies subject by subject, performance of these two weighting systems depends on the extent of correlation among sites within each subject. In this paper, we describe a new weighting method that minimizes the variance of the estimator. We apply these methods to data from a study involving an enzymatic diagnostic test to illustrate the estimation of the sensitivity and the specificity of periodontal diagnostic tests. Simulation studies were conducted to compare the performance of the new estimator with that of other estimators.",
keywords = "Intraclass correlation, Optimal weight, Sensitivity, Specificity",
author = "Jung, {Sin ho} and Chul Ahn",
year = "2000",
doi = "10.1177/009286150003400228",
language = "English (US)",
volume = "34",
pages = "599--604",
journal = "Therapeutic Innovation and Regulatory Science",
issn = "2168-4790",
publisher = "SAGE Publications Inc.",
number = "2",

}

TY - JOUR

T1 - Estimation of response probability in correlated binary data

T2 - A new approach

AU - Jung, Sin ho

AU - Ahn, Chul

PY - 2000

Y1 - 2000

N2 - We consider analysis of binary observations from multiple sites of each subject. In this case, observations from the same subject tend to be correlated. In estimating the common response probability in correlated binary data, two weighting systems have been most popular: equal weights to sites, and equal weights to subjects. When the number of sites varies subject by subject, performance of these two weighting systems depends on the extent of correlation among sites within each subject. In this paper, we describe a new weighting method that minimizes the variance of the estimator. We apply these methods to data from a study involving an enzymatic diagnostic test to illustrate the estimation of the sensitivity and the specificity of periodontal diagnostic tests. Simulation studies were conducted to compare the performance of the new estimator with that of other estimators.

AB - We consider analysis of binary observations from multiple sites of each subject. In this case, observations from the same subject tend to be correlated. In estimating the common response probability in correlated binary data, two weighting systems have been most popular: equal weights to sites, and equal weights to subjects. When the number of sites varies subject by subject, performance of these two weighting systems depends on the extent of correlation among sites within each subject. In this paper, we describe a new weighting method that minimizes the variance of the estimator. We apply these methods to data from a study involving an enzymatic diagnostic test to illustrate the estimation of the sensitivity and the specificity of periodontal diagnostic tests. Simulation studies were conducted to compare the performance of the new estimator with that of other estimators.

KW - Intraclass correlation

KW - Optimal weight

KW - Sensitivity

KW - Specificity

UR - http://www.scopus.com/inward/record.url?scp=84996149271&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84996149271&partnerID=8YFLogxK

U2 - 10.1177/009286150003400228

DO - 10.1177/009286150003400228

M3 - Article

AN - SCOPUS:84996149271

VL - 34

SP - 599

EP - 604

JO - Therapeutic Innovation and Regulatory Science

JF - Therapeutic Innovation and Regulatory Science

SN - 2168-4790

IS - 2

ER -