Latent Class Modeling Approaches for Assessing Diagnostic Error without a Gold Standard: With Applications to p53 Immunohistochemical Assays in Bladder Tumors

Journal article

Peer reviewed

Paul S Albert, Lisa M McShane, Joanna H Shih and US Natl Canc Inst Bladder Tumor Ma

Biometrics, Vol.57(2), pp.610-619

Received April 2000. Revised September 2000. Accepted September 2000.

2001-06

PMID: 11414591

Abstract

Biomarkers

Misclassification

Repeated binary data

Sensitivity

Specificity

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Citation topics: 1 Clinical & Life Sciences; 1.175 Medical Physics; 1.175.1231 Pacs
Web Of Science research areas: Biology; Mathematical & Computational Biology; Statistics & Probability
ESI research areas: Mathematics

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Source: InCites

Title: Latent Class Modeling Approaches for Assessing Diagnostic Error without a Gold Standard: With Applications to p53 Immunohistochemical Assays in Bladder Tumors
Creators: Paul S Albert - Biometric Research Branch, National Cancer Institute, Executive Plaza North, Room 739, Bethesda, Maryland 20892-7434, U.S.A
Lisa M McShane - Biometric Research Branch, National Cancer Institute, Executive Plaza North, Room 739, Bethesda, Maryland 20892-7434, U.S.A
Joanna H Shih - Office of Biostatistics Research, National Heart, Lung, and Blood Institute, Bethesda, Maryland 20892, U.S.A
US Natl Canc Inst Bladder Tumor Ma
Publication Details: Biometrics, Vol.57(2), pp.610-619
Publisher: Blackwell Publishing Ltd
Edition: Received April 2000. Revised September 2000. Accepted September 2000.
Number of pages: 10
Language: English
Resource Type: Journal article
PMID: 11414591
Record Identifier: 991031613133102976