Detecting Rating Scale Malfunctioning With the Partial Credit Model and Generalized Partial Credit Model
1The University of Alabama, Tuscaloosa, USA.
Educational and Psychological Measurement
|September 4, 2023
Summary
Rating scale analysis techniques, using partial credit models (PCM) and generalized partial credit models (GPCM), effectively identify rating scale issues. Both models aid researchers in understanding scale functioning and detecting potential problems.
Area of Science:
- Psychometrics
- Educational Measurement
- Quantitative Psychology
Background:
- Ordinal rating scales are widely used in research.
- Effective use requires scales to function psychometrically.
- Limited research explores scale "malfunctioning" sensitivity.
Purpose of the Study:
- To systematically explore the sensitivity of rating scale analysis techniques.
- To investigate two popular polytomous item response theory (IRT) models: PCM and GPCM.
- To assess model sensitivity to rating scale malfunctioning.
Main Methods:
- Utilized a real data analysis.
- Conducted a simulation study.
- Applied partial credit model (PCM) and generalized partial credit model (GPCM).
Main Results:
- Both PCM and GPCM provide valuable insights into rating scale threshold ordering and precision.
- The models help researchers understand scale functioning.
- Differences in model sensitivity to malfunctioning were observed under specific conditions.
Conclusions:
- Rating scale analysis techniques, particularly PCM and GPCM, are useful for evaluating scale psychometric properties.
- These methods assist in identifying areas for scale improvement.
- Researchers can leverage IRT models to detect and address rating scale issues.
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