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Updated: Jul 16, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Test for increasing convex order in multivariate response.

Yanqin Feng¹, Jinde Wang

¹School of Mathematics and Statistics, Wuhan University, Wuhan 430072, PR China. yangf2008@yahoo.com.cn

Biometrical Journal. Biometrische Zeitschrift

|March 9, 2007

Summary

This study introduces a new statistical test for dose-response data with ordered categories. The model-free method addresses limitations of existing tests for binary outcomes, offering broader applicability in medical research.

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Last Updated: Jul 16, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Area of Science:

Biostatistics
Medical Statistics
Statistical Inference

Background:

Dose-response trend testing is crucial in medicine, but existing methods primarily support binary outcomes.
Binary response methods face challenges with data dichotomization and may not capture nuanced trends.
Statistical inference for ordered categorical multivariate responses, particularly the increasing convex order, remains underdeveloped for multiple populations.

Purpose of the Study:

To develop a novel, model-free statistical test for increasing convex order in dose-response studies.
To extend trend testing capabilities beyond binary responses to multivariate, ordered categorical data.
To provide a flexible method applicable to two-way tables and stratified medical data.

Main Methods:

A model-free statistical test is proposed for assessing the increasing convex order alternative.
The method is designed for cross-classified data, accommodating multivariate responses with ordered categories.
The approach is suitable for two-way tables and stratified data structures.

Main Results:

The developed test provides a method for statistical inference on increasing convex order.
It overcomes limitations of existing methods that are restricted to binary response variables.
The test is applicable to situations with more than two multinomial populations.

Conclusions:

The proposed model-free test offers a significant advancement for dose-response trend analysis with ordered categorical data.
This method enhances statistical inference capabilities in medical research where complex response patterns are common.
The approach is demonstrated with real-world examples, highlighting its practical utility.