9 citations · 9 across the 4 of their papers we have counts for
6 papers
The generalized underlap coefficient with an application in clustering
Zhaoxi Zhang, Vanda Inácio, Sara Wade
Quantifying distributional separation across groups is fundamental in statistical learning and scientific discovery, yet most classical discrepancy measures are tailored to two-gro…
Likelihood-based Modeling of Covariate-Specific Time-Dependent ROC Curves
Ainesh Sewak, Vanda Inacio, Joanne Wuu +2
Identifying reliable biomarkers for predicting clinical events in longitudinal studies is important for accurate disease prognosis and for guiding development of new treatments. Ho…
Bayesian dependent mixture models: A predictive comparison and survey
Sara Wade, Vanda Inacio, Sonia Petrone
For exchangeable data, mixture models are an extremely useful tool for density estimation due to their attractive balance between smoothness and flexibility. When additional covari…
Robust and flexible inference for the covariate-specific ROC curve
Vanda Inacio, Vanda M. Lourenco, Miguel de Carvalho +2
Diagnostic tests are of critical importance in health care and medical research. Motivated by the impact that atypical and outlying test outcomes might have on the assessment of th…
Statistical Evaluation of Medical Tests
Vanda Inacio, Maria Xose Rodriguez-Alvarez, Pilar Gayoso-Diz
In this review, we present an overview of the main aspects related to the statistical evaluation of medical tests for diagnosis and prognosis. Measures of diagnostic performance fo…
ROCnReg: An R Package for Receiver Operating Characteristic Curve Inference with and without Covariate Information
Maria Xose Rodriguez-Alvarez, Vanda Inacio
The receiver operating characteristic (ROC) curve is the most popular tool used to evaluate the discriminatory capability of diagnostic tests/biomarkers measured on a continuous sc…