Abstract
The purpose of this study was to investigate within- and between-threshold parameter invariance for items of a fourteen-item Positive Affect Scale developed to assess positive moods (like happy, peaceful, etc.) of university students. To test whether the estimated threshold parameters were as expected (1 to 5, with increments of 1) across all the 14 items, Graded Response, Partial Credit, and Rating Scale Models were fit the response data collected from 326 students. A comparison of the model fit statistics, such as the negative 2log likelihood and chi-square values, revealed that the Graded Response Model had the best fit and that the thresholds estimates for all the items in the Positive Affective Scale were reasonably close to the expected 1 to 5 values with increments of 1. The study illustrates how polytomous response models can be used to test the psychometric quality of items with ordinal rating scales.
Highlights
When the response scales of the polytomous scored items are formulated, e.g., Likert scale, it is expected that respondents will choose the category that best describes their state given the measured trait
Polytomous Item Response Theory (IRT) models, commonly used in calibrating items of most cognitive assessment tools, are yet to gain such common use when it comes to calibrating ordinal rating scale items, which are often used in the evaluation of psychological constructs, such as personality traits (Baker, Rounds, & Zevon, 2000)
These results show that Graded Response Model (GRM) and Rating Scale Model (RSM) fitted the data better than Partial Credit Model (PCM)
Summary
When the response scales of the polytomous scored items are formulated, e.g., Likert scale, it is expected that respondents will choose the category that best describes their state given the measured trait. Researchers studying traits from the affective domain do often face a greater number of challenges when evaluating the quality of their assessment results when compared to those who study traits from the cognitive domain, yet new methodological advancements rarely target their issues first. In this context, polytomous Item Response Theory (IRT) models, commonly used in calibrating items of most cognitive assessment tools, are yet to gain such common use when it comes to calibrating ordinal rating scale items, which are often used in the evaluation of psychological constructs, such as personality traits (Baker, Rounds, & Zevon, 2000). Given that assessment tools assessing psychological characteristics are, in general, composed of rating scale items, it would be most reasonable that polytomous IRT models are used in estimating non-linear relationships between the
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