| Evaluating accuracy of diagnostic tests with intermediate results in the absence of a gold standard. | |
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MedLine Citation:
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PMID: 23212851 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Intermediate test results often occur with diagnostic tests. When assessing diagnostic accuracy, it is important to properly report and account for these results. In the literature, these results are commonly discarded prior to analysis or treated as either a positive or a negative result. Although such adjustments allow sensitivity and specificity to be computed in the standard way, these forced decisions limit the interpretability and usefulness of the results. Estimation of diagnostic accuracy is further complicated when tests are evaluated without a gold standard. Although traditional latent class modeling can be readily applied to analyze these data and account for intermediate results, these models assume that tests are independent conditional on the true disease status, which is rarely valid in practice. We extend both the log-linear latent class model and the probit latent class model to accommodate the conditional dependence among tests while taking the intermediate results into consideration. We illustrate our methods using a simulation study and a published medical study on the detection of epileptiform activity in the brain. Copyright © 2012 John Wiley & Sons, Ltd. |
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Authors:
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Huiping Xu; Michael A Black; Bruce A Craig |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-12-5 |
Journal Detail:
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Title: Statistics in medicine Volume: - ISSN: 1097-0258 ISO Abbreviation: Stat Med Publication Date: 2012 Dec |
Date Detail:
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Created Date: 2012-12-5 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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Copyright © 2012 John Wiley & Sons, Ltd. |
Affiliation:
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Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN 46020, U.S.A. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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