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Updated: Jul 11, 2026
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A Two-interval Forced-choice Task for Multisensory Comparisons
Published on: November 9, 2018
The mathematical relationship among different forms of responsiveness coefficients
G R Norman1, Kathleen W Wyrwich, Donald L Patrick
1Department of Clinical Epidemiology and Biostatistics, MDCL 3519, McMaster University, Hamilton, ON, L8N 3Z5, Canada. norman@mcmaster.ca
Summary
This study clarifies responsiveness measures in health research. Cohen's effect size and the Standardized Response Mean are recommended, but Cohen's effect size ensures better interpretability and comparability.
Area of Science:
- Health Outcomes Research
- Psychometrics
- Statistical Analysis
Background:
- Lack of consensus on the optimal measure of responsiveness in health research.
- Existing indices are often variants of Cohen's effect size, with unclear mathematical relationships.
- Inconsistent use of responsiveness measures complicates interpretation in health-related quality of life (HRQL) studies.
Purpose of the Study:
- To analytically elucidate the mathematical relationships among common indices of responsiveness.
- To identify the most appropriate measures for assessing change in health outcomes.
- To provide guidance for consistent and interpretable analysis of responsiveness.
Main Methods:
- Mathematical analysis of variance components underlying change scores.
- Analytical derivation of relationships between different responsiveness indices.
- Evaluation of the properties and interpretability of various statistical measures.
Main Results:
- Cohen's effect size and the Standardized Response Mean are identified as the most appropriate measures.
- Each recommended measure provides unique information regarding treatment effect and response variability.
- Measures based on variability in change scores can be misleading under certain conditions.
Conclusions:
- Cohen's effect size and the Standardized Response Mean offer valuable insights into treatment effects.
- The Standardized Response Mean requires cautious interpretation due to potential misleading information.
- Future research should prioritize Cohen's effect size for enhanced interpretability and comparability in responsiveness analysis.
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