2 citations · 3 across the 11 of their papers we have counts for
5 papers · 1 filter
Semiparametric Receiver Operating Characteristic Analysis in the Presence of an Imperfect Reference Standard via a Box-Cox Density Ratio Model
Yi Chang, Siyan Liu, Qinglong Tian +1
Receiver operating characteristic (ROC) analysis is commonly used to evaluate the diagnostic accuracy of continuous biomarkers. In practice, the true disease status may be unavaila…
In-Context Positive-Unlabeled Learning
Siyan Liu, Yi Chang, Manli Cheng +2
Positive-unlabeled (PU) learning addresses binary classification when only a set of labeled positives is available alongside a pool of unlabeled samples drawn from a mixture of pos…
A goodness-of-fit test for the logistic propensity score model under nonignorable missing data
Manli Cheng, Yangjianchen Xu, Qinglong Tian +1
Logistic regression is widely used to model the propensity score in the analysis of nonignorable missing data. However, goodness-of-fit testing for this propensity score model has…
Neyman-Pearson multiclass classification under label noise via empirical likelihood
Qiong Zhang, Qinglong Tian, Pengfei Li
In many classification problems, misclassification costs are highly asymmetric, while training labels are often corrupted due to measurement error, annotator variability, or advers…
Semiparametric Joint Inference for Sensitivity and Specificity at the Youden-Optimal Cut-Off
Siyan Liu, Qinglong Tian, Chunlin Wang +1
Sensitivity and specificity evaluated at an optimal diagnostic cut-off are fundamental measures of classification accuracy when continuous biomarkers are used for disease diagnosis…