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Evidence-based practice for equating health status items: sample size and IRT model.
Karon F Cook1, Patrick W Taylor, Barbara G Dodd
1University of Washington. karonc2@u.washington.ed
Journal of Applied Measurement
|April 19, 2007
Summary
Sample size significantly impacts health outcome measure equating quality, with less than 300 participants being unacceptable. Test size had minimal effect on equating accuracy.
Area of Science:
- Health outcomes research
- Psychometrics
- Health status measurement
Background:
- Health outcome measures often use multiple forms to distribute response burden across samples.
- This leads to non-equivalent scores requiring statistical equating to a common metric.
Purpose of the Study:
- To investigate the influence of sample size, test size, and item response theory (IRT) model selection on equating accuracy.
- Focus on equating three forms of a health status measure with unique and anchor items.
Main Methods:
- Secondary data analysis of patient responses to the Health of Seniors Survey developmental item pool.
- Utilized a completely crossed design with 25 replications per study cell.
Main Results:
- Equating quality was highly sensitive to sample size, more so than the choice of IRT model.
- Equating based on 60 or 72 items showed little to no advantage over 48 items.
Conclusions:
- Sample sizes below 300 are insufficient for reliable equating of multiple health outcome measure forms.
- Provides evidence-based sample size recommendations for future equating studies.
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