Logo image
What do measures of agreement (kappa) tell us about quality of exposure assessment? Theoretical analysis and numerical simulation
Journal article   Open access   Peer reviewed

What do measures of agreement (kappa) tell us about quality of exposure assessment? Theoretical analysis and numerical simulation

Igor Burstyn, Frank de Vocht and Paul Gustafson
BMJ open, v 3(12), pp e003952-e003952
01 Jan 2013
PMID: 24302507
url
https://doi.org/10.1136/bmjopen-2013-003952View
Published, Version of Record (VoR)CC BY-NC V4.0 Open

Abstract

General & Internal Medicine Life Sciences & Biomedicine Medicine, General & Internal Science & Technology
Background: The reliability of binary exposure classification methods is routinely reported in occupational health literature because it is viewed as an important component of evaluating the trustworthiness of the exposure assessment by experts. The Kappa statistics (kappa) are typically employed to assess how well raters or classification systems agree in a variety of contexts, such as identifying exposed participants in a population-based epidemiological study of risks due to occupational exposures. However, the question we are really interested in is not so much the reliability of an exposure assessment method, although this holds value in itself, but the validity of the exposure estimates. The validity of binary classifiers can be expressed as a method's sensitivity (SN) and specificity (SP), estimated from its agreement with the error-free classifier. Methods and results: We describe a simulation-based method for deriving information on SN and SP that can be derived from. and the prevalence of exposure, since an analytic solution is not possible without restrictive assumptions. This work is illustrated in the context of comparison of job-exposure matrices assessing occupational exposures to polycyclic aromatic hydrocarbons. Discussion: Our approach allows the investigators to evaluate how good their exposure-assessment methods truly are, not just how well they agree with each other, and should lead to incorporation of information of validity of expert assessment methods into formal uncertainty analyses in epidemiology.

Metrics

2 Record Views
10 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Public, Environmental & Occupational Health
Logo image