title: Adjusting for non-ignorable verification bias in clinical studies for Alzheimer's disease.
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.
authors.affiliation: Department of Biostatistics, University of Washington, F600 HSB Box # 357232, Seattle, WA 98195-7232, USA. azhou@u.washington.edu
authors.forename: Xiao-Hua
authors.initials: XH
authors.lastname: Zhou
authors.forename: Pete
authors.initials: P
authors.lastname: Castelluccio
mesh_terms: D000544:Alzheimer Disease / Q000175:diagnosis*; D015982:Bias; D006801:Humans; D016013:Likelihood Functions; D012372:ROC Curve