Related Experiment Video
Updated: Jan 15, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Nonparametric Inference for the Covariate-Adjusted Youden Index and Associated Cut-Off Points for Three Ordinal
Asieh Maghami-Mehr1, Hamzeh Torabi1, Hossein Nadeb1
1Department of Statistics, Yazd University, Yazd, Iran.
Abstract:
In this paper, we propose point estimators and confidence intervals for the Youden index and optimal cut-off points in the context of three ordinal diagnostic groups, accounting for the presence of covariates. Using heteroscedastic regression models, we introduce two point estimators based on different assumptions and examine their asymptotic properties. Additionally, we present confidence intervals for the covariate-adjusted Youden index and its corresponding optimal cut-off points. The performance of the proposed estimators and confidence intervals is evaluated through a Monte Carlo simulation study. Finally, we demonstrate the applicability of our methods to an Alzheimer's disease dataset.
More Related Videos
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Friedman Two-way Analysis of Variance by Ranks
The Mantel-Cox Log-Rank Test
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Receiver Operating Characteristic Plot
Wilcoxon Rank-Sum Test

