Literature DB >> 14716724

Adjusting for non-ignorable verification bias in clinical studies for Alzheimer's disease.

Xiao-Hua Zhou1, Pete Castelluccio.   

Abstract

A common problem for comparing the relative accuracy of two screening tests for Alzheimer's disease (AD) in a two-stage design study is verification bias. If the verification bias can be assumed to be ignorable, Zhou and Higgs have proposed a maximum likelihood approach to compare the relative accuracy of screening tests in a two-stage design study. However, if the verification mechanism also depends on the unobserved disease status, the ignorable assumption does not hold. In this paper, we discuss how to use a profile likelihood approach to compare the relative accuracy of two screening tests for AD without assuming the ignorable verification bias mechanism. Copyright 2004 John Wiley & Sons, Ltd.

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Year:  2004        PMID: 14716724     DOI: 10.1002/sim.1711

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  A regression approach to ROC surface, with applications to Alzheimer's disease.

Authors:  Jialiang Li; Andrew Xiaohua Zhou; Jason P Fine
Journal:  Sci China Math       Date:  2012-08       Impact factor: 1.331

2.  A model for adjusting for nonignorable verification bias in estimation of the ROC curve and its area with likelihood-based approach.

Authors:  Danping Liu; Xiao-Hua Zhou
Journal:  Biometrics       Date:  2010-12       Impact factor: 2.571

Review 3.  Estimation of diagnostic test accuracy without full verification: a review of latent class methods.

Authors:  John Collins; Minh Huynh
Journal:  Stat Med       Date:  2014-06-09       Impact factor: 2.373

  3 in total

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