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A Multilevel Bifactor Approach to Construct Validation of Mixed-Format Scales
Yan Wang1, Eun Sook Kim1, Robert F Dedrick1
1University of South Florida, Tampa, FL, USA.
Educational and Psychological Measurement
|May 26, 2018
Summary
Wording effects in surveys can bias results. A new multilevel bifactor model accurately accounts for these effects in mixed-format scales, improving validity at the between-level.
Area of Science:
- Psychometrics
- Educational Measurement
- Quantitative Psychology
Background:
- Wording effects in scales, stemming from positively and negatively worded items, can compromise construct validity and introduce systematic bias.
- Existing models like the correlated uniqueness model and correlated traits and correlated methods model have been used to address these effects.
- Mixed-format scales in multilevel contexts present unique challenges for handling wording effects.
Purpose of the Study:
- To introduce and illustrate a multilevel bifactor approach for addressing wording effects in mixed-format scales within a multilevel context.
- To compare the performance of the multilevel bifactor model against other models in handling wording effects.
- To examine the impact of ignoring wording effects on the validity of scales at different levels.
Main Methods:
- Application of a multilevel bifactor model to the Students Confident in Mathematics scale.
- Comparison of the multilevel bifactor model with alternative models to assess wording effects.
- Analysis of wording effects at both within-level and between-level data structures.
Main Results:
- Positive and negative wording effects were detected at both within and between levels of analysis.
- Ignoring wording effects minimally impacted the within-level predictive validity of the Students Confident in Mathematics scale.
- Ignoring wording effects significantly reduced the between-level validity coefficient, highlighting its importance.
Conclusions:
- The multilevel bifactor approach effectively handles wording effects in mixed-format scales within multilevel data.
- Researchers must consider wording effects, especially at the between level, to ensure accurate interpretation of scale validity.
- The findings have significant implications for applied researchers using mixed-format scales in multilevel settings.
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