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Evaluation of the link between the Guttman errors and response shift at the individual level
Yseulys Dubuy1, Véronique Sébille2, Marie Grall-Bronnec2,3
1INSERM U1246, SPHERE University of Nantes, University of Tours, Nantes, France. Yseulys.Dubuy@univ-nantes.fr.
Summary
Guttman errors (GEs) may help detect individual response shift (RS) over time. Simulations show recalibration RS increases GEs, suggesting GEs as a potential tool for individual RS detection, though further research is needed.
Area of Science:
- Psychometrics
- Health Outcomes Research
- Statistical Modeling
Background:
- Response shift (RS) presents challenges in analyzing patient-reported outcomes over time.
- Individual-level RS detection methods are crucial for accurate longitudinal data analysis.
- Guttman errors (GEs) measure response discrepancies and may indicate RS.
Purpose of the Study:
- To investigate the link between recalibration RS and changes in the number of GEs over time.
- To evaluate the potential of the GE change index ([Formula: see text]) for detecting individual-level RS.
- To explore the discriminating ability of this index in simulations.
Main Methods:
- Simulated patient responses with and without recalibration RS.
- Calculated the change in the number of GEs over time for simulated individuals.
- Investigated the influence of sample, questionnaire, and recalibration parameters.
Main Results:
- Simulated individuals with recalibration showed a greater average increase in GEs over time compared to those without RS.
- Questionnaire structure and recalibration magnitude significantly impacted the GE change index.
- The overall discriminating ability of the index for RS detection was found to be low.
Conclusions:
- Evidence suggests a relationship between recalibration RS and increased GEs.
- Guttman errors show promise as a nonparametric tool for individual-level RS detection.
- Further research is necessary to validate and refine the use of GEs for RS detection.
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