No abstract

The Youden index is a widely used measure in the framework of medical diagnostics, where the effectiveness of a biomarker (screening marker or predictor) for classifying a disease status is studied. When the biomarker is continuous, it is important to determine the threshold or cut-off point to be used in practice for the discrimination between diseased and healthy populations. We introduce two methods aimed at estimating the Youden index and its associated threshold. The first one is a modified version of a recent approach based on the delta method, and the second one is based on the adjusted empirical likelihood for quantiles in the setting of a two-sample problem. We also include CIs for both of them. In the simulation study, we compare both methods under different scenarios. Finally, a real example of prostatic cancer, well known in the literature, is analysed to provide the reader with a better understanding of the new methodology.

Continuous diagnostic tests are often used for discriminating between healthy and diseased populations. For this reason, it is useful to select an appropriate discrimination threshold. There are several optimality criteria: the North-West corner, the Youden index, the concordance probability and the symmetry point, among others. In this paper, we focus on the symmetry point that maximizes simultaneously the two types of correct classifications. We construct confidence intervals for this optimal cutpoint and its associated specificity and sensitivity indexes using two approaches: one based on the generalized pivotal quantity and the other on empirical likelihood. We perform a simulation study to check the practical behaviour of both methods and illustrate their use by means of three real biomedical datasets on melanoma, prostate cancer and coronary artery disease.

In this paper we describe 10 expressions of score and weighted tests, in such a way that the numerators and the denominators are completely specified, including always the possibility of tied observations. We establish the equivalence between score and weighted tests in the general setting of ties. Based upon this equivalence we enunciate two new tests, which complete the jigsaw of the classification of these non-parametric tests in Survival Analysis.

In this paper we will give the relationships of several Score tests and Weighted tests for right censoring data with other classical tests. Special care will be taken with the case of ties and with the kind of estimation of the variance used. After the description of ten tests, a comparative study will be made among them. Finally, an application with a real example will be included.