Nonparametric ROC summary statistics for correlated diagnostic marker data
نویسندگان
چکیده
منابع مشابه
Nonparametric ROC summary statistics for correlated diagnostic marker data.
We propose efficient nonparametric statistics to compare medical imaging modalities in multi-reader multi-test data and to compare markers in longitudinal ROC data. The proposed methods are based on the weighted area under the ROC curve, which includes the area under the curve and the partial area under the curve as special cases. The methods maximize the local power for detecting the differenc...
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Receiver Operating Characteristic (ROC) analysis is one of the most widely used methods for summarizing intrinsic properties of a diagnostic system, and is often used in evaluation and comparison of diagnostic technologies, practices or systems. These methods play an important role in public health since they enable researchers to achieve a greater insight into the properties of diagnostic test...
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References Gleason, J. R. 1997. ip18: A command for randomly resampling a dataset. Stata Technical Bulletin 37: 17–22. Reprinted in Stata Technical Bulletin Reprints, vol. 7, pp. 77–83. ——. 1999. ip18.1: Update to resample. Stata Technical Bulletin 52: 9–10. Reprinted in Stata Technical Bulletin Reprints, vol. 9, p. 119. Weesie, J. 1997. dm46: Enhancement to the sample command. Stata Technical ...
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ROC curves are a popular method for displaying sensitivity and specificity of a continuous diagnostic marker, X, for a binary disease variable, D. However, many disease outcomes are time dependent, D(t), and ROC curves that vary as a function of time may be more appropriate. A common example of a time-dependent variable is vital status, where D(t) = 1 if a patient has died prior to time t and z...
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ژورنال
عنوان ژورنال: Statistics in Medicine
سال: 2012
ISSN: 0277-6715
DOI: 10.1002/sim.5654