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Are the Steps on Likert Scales Equidistant? Responses on Visual Analog Scales Allow Estimating Their Distances
1Universidad Complutense, Madrid, Spain.
Educational and Psychological Measurement
|January 22, 2024
Summary
Likert scale steps are not equal. This study introduces a method using visual analog scales (VAS) and item response theory to measure the true distances between Likert response options, revealing unequal intervals.
Area of Science:
- Psychometrics
- Quantitative Psychology
- Statistical Modeling
Background:
- Likert items are widely used but their discrete steps may not represent equal intervals on an underlying continuum.
- This assumption of equal intervals is crucial for accurate data interpretation and analysis.
- Traditional methods lack direct ways to assess the equality of intervals in Likert response formats.
Purpose of the Study:
- To develop and validate a method for estimating the distances between consecutive steps of Likert items.
- To investigate the assumption of equal intervals in Likert scales using item response theory.
- To explore the implications for scoring Likert-based measurements.
Main Methods:
- Utilized item response theory, specifically the Continuous Response Model (CRM) and Graded Response Model (GRM).
- Administered items in both Likert and Visual Analog Scale (VAS) formats to capture continuous response data.
- Established a formal relationship between CRM and GRM parameters to estimate interval boundaries.
Main Results:
- Demonstrated a valid method for estimating interval distances through simulation studies.
- Empirical analysis of personality scale data confirmed the correspondence between VAS and Likert formats.
- Revealed significant and variable unequal distances between successive Likert scale steps across different items.
Conclusions:
- The assumption of equal intervals for Likert scale steps is often violated.
- The proposed method provides a quantitative approach to assess and understand interval properties of Likert items.
- Findings have important implications for the accurate scoring and interpretation of Likert scale data in research and practice.
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