Assessing measurement error in surveys using latent class analysis: application to self-reported illicit drug use in data from the Iranian Mental Health Survey

Assessing measurement error in surveys using latent class analysis: application to self-reported illicit drug use in data from the Iranian Mental Health Survey

Latent class analysis (LCA) is a method of assessing and correcting measurement error in surveys. The local independence assumption in LCA assumes that indicators are independent from each other condition on the latent variable. Violation of this assumption leads to unreliable results. We explored t...

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Bibliographic Details
Main Authors: Kazem Khalagi, Mohammad Ali Mansournia, Afarin Rahimi-Movaghar, Keramat Nourijelyani, Masoumeh Amin-Esmaeili, Ahmad Hajebi, Vandad Sharif, Reza Radgoodarzi, Mitra Hefazi, Abbas Motevalian
Format: Article
Language:English
Published: Korean Society of Epidemiology 2016-04-01
Series:Epidemiology and Health
Subjects:
Surveys and questionnaires
Bias
Outcome measurement errors
Latent class analysis
Self report
Substance-related disorders
Online Access:http://www.e-epih.org/upload/pdf/epih-38-e2016013.pdf

Internet

http://www.e-epih.org/upload/pdf/epih-38-e2016013.pdf

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