title: Modelling population heterogeneity in sensitivity and specificity of a multi-stage screen for obstructive sleep apnoea.
abstract: We propose a model-based approach for modelling population heterogeneity in terms of sensitivity and specificity of multi-stage screening procedures that consists of multiple tests ordered according to criteria such as cost and invasiveness. It is assumed that a patient proceeds to the next test only if they test positive for the current test. An overall positive result occurs if a patient tests positive for all tests. A dropout occurs when a subject tests positive for a test but does not proceed to subsequent tests. Chinchilli proposed estimates of sensitivity and specificity based upon ratios of multinomial sample probabilities for such a multi-stage procedure in a homogeneous population. The method proposed here accommodates population heterogeneity with generalized linear models and transformation-based confidence intervals. In contrast to the approach of Chinchilli, such an approach provides model-based tests of population differences, narrower confidence intervals that satisfy boundary constraints, and a method for accommodating dropouts without the need for prespecified weights. The proposed method is motivated by the need to assess age differences in the accuracy of a multi-stage test for obstructive sleep apnoea.
authors.affiliation: Center for Biostatistics and Epidemiology, Pennsylvania State University, Hershey 17033, USA.
authors.forename: T R
authors.initials: TR
authors.lastname: ten Have
authors.forename: E O
authors.initials: EO
authors.lastname: Bixler
mesh_terms: D000328:Adult; D016001:Confidence Intervals; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening; D015233:Models, Statistical; D010352:Patient Dropouts; D016016:Proportional Hazards Models; D012680:Sensitivity and Specificity; D012891:Sleep Apnea Syndromes / Q000175:diagnosis*; D018709:Statistics, Nonparametric