scholarly journals Bias–corrected methods for estimating the receiver operating characteristic surface of continuous diagnostic tests

2016 ◽  
Vol 10 (2) ◽  
pp. 3063-3113 ◽  
Author(s):  
Khanh To Duc ◽  
Monica Chiogna ◽  
Gianfranco Adimari
Keyword(s):  
Receiver Operating Characteristic ◽  
Diagnostic Tests ◽  
Operating Characteristic ◽  
Characteristic Surface ◽  
Receiver Operating

Estimation of the volume under the receiver-operating characteristic surface adjusting for non-ignorable verification bias

2018 ◽  
Vol 27 (3) ◽  
pp. 715-739 ◽  
Author(s):  
Ying Zhang ◽  
Todd A Alonzo ◽  
Keyword(s):  
Receiver Operating Characteristic ◽  
Diagnostic Test ◽  
Operating Characteristic ◽  
Disease Status ◽  
Characteristic Surface ◽  
Finite Sample ◽  
Classification Problems ◽  
Verification Bias ◽  
Inverse Probability Weighted ◽  
Receiver Operating

The receiver-operating characteristic surface is frequently used for presenting the accuracy of a diagnostic test for three-category classification problems. One common problem that can complicate the estimation of the volume under receiver-operating characteristic surface is that not all subjects receive the verification of the true disease status. Estimation based only on data from subjects with verified disease status may be biased, which is referred to as verification bias. In this article, we propose new verification bias correction methods to estimate the volume under receiver-operating characteristic surface for a continuous diagnostic test. We assume the verification process is missing not at random, which means the missingness might be related to unobserved clinical characteristics. Three classes of estimators are proposed, namely, inverse probability weighted, imputation-based, and doubly robust estimators. A jackknife estimator of variance is derived for all the proposed volume under receiver-operating characteristic surface estimators. The finite sample properties of the new estimators are examined via simulation studies. We illustrate our methods with data collected from Alzheimer’s disease research.

scholarly journals Tree-structured Subgroup Analysis of Receiver Operating Characteristic Curves for Diagnostic Tests

2012 ◽  
Vol 19 (12) ◽  
pp. 1529-1536 ◽  
Author(s):  
Caixia Li ◽  
Claus-C. Glüer ◽  
Richard Eastell ◽  
Dieter Felsenberg ◽  
David M. Reid ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Subgroup Analysis ◽  
Diagnostic Tests ◽  
Operating Characteristic ◽  
Characteristic Curves ◽  
Receiver Operating Characteristic Curves ◽  
Receiver Operating
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