Examining statistical disclosure issues involving digital images of ROC curves

被引:0
|
作者
Matthews, Gregory J. [1 ]
Harel, Ofer [2 ]
机构
[1] Loyola Univ Chicago, Dept Math & Stat, 1032 W Sheridan Rd, Chicago, IL 60660 USA
[2] Univ Connecticut, Dept Stat, Storrs, CT 06269 USA
来源
STAT | 2015年 / 4卷 / 01期
关键词
missing data; privacy; ROC analysis; sensitivity; specificity; statistical disclosure control;
D O I
10.1002/sta4.93
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
It has been established that knowing the true values of the empirical receiver operating characteristic (ROC) curve (i.e. false-positive and true-positive rate pairs for all thresholds) along with a subset of the full data set consisting of n - 1 observations can cause unwanted disclosures. Here, we explore a similar problem with two main extensions. First, rather than knowledge of the true values of the empirical ROC curve, we start only with an image of the empirical ROC curve. Second, rather than considering only subsets of n - 1, we look at several differently sized subsets. Given this information (i.e. empirical ROC image and a subset of the full data set), we experimentally act as a data snooper and explore what can be learned about unobserved portions of the full data set. Copyright (C) 2015 John Wiley & Sons, Ltd.
引用
收藏
页码:235 / 245
页数:11
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