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Hidden Variance in Multiple Mini-Interview Scores

Zaidi, Nikki
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427797882

Abstract Details

2015, PhD, University of Cincinnati, Education, Criminal Justice, and Human Services: Educational Studies.
The extant literature has largely ignored a potentially significant source of variance in Multiple Mini-Interview (MMI) scores by ignoring, or “hiding,” the variance attributable to the sample of attributes used on an evaluation form. This potential source of error variance can be defined as the rating items, commonly referred to as sub-scores, which typically comprise an MMI evaluation form. Due to its multi-faceted, repeated measures format, reliability for the MMI has been primarily evaluated using Generalizability (G) theory. A key assumption of G theory is that G studies model the most important sources of error variance to which a researcher plans to generalize. Because G studies can only attribute error variance to the facets that are modeled in a G study, failure to model potentially substantial sources of error variance can result in biased estimates of variance components. This study demonstrates the implications of failing to model the item facet when true item-level effects exist. An extensive Monte Carlo simulation study was performed to examine whether a commonly used hidden item G study design (p x s|i) results in biased estimated variance components. Estimates from this model, which was hypothesized to be incorrectly specified, were compared with estimates from a more complete person-by-station-by-item (p x s x i) model, which was hypothesized to be correctly specified. Results suggest that the hidden item G study design (p x s|i) will result in biased variance component and reliability estimates; therefore, researchers should consider using the more complete person-by-station-by-item (p x s x i) model.
Christopher Swoboda, Ph.D. (Committee Chair)
R.Stephen Manuel, Ph.D. (Committee Member)
Benjamin Kelcey, Ph.D. (Committee Member)
188 p.
Educational Evaluation
Generalizability theory; Multiple Mini-Interview; Monte Carlo simulation; variance component estimates; medical school interviews; MMI

Recommended Citations

Citations

  • Zaidi, N. (2015). Hidden Variance in Multiple Mini-Interview Scores [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427797882

    APA Style (7th edition)

  • Zaidi, Nikki. Hidden Variance in Multiple Mini-Interview Scores. 2015. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427797882.

    MLA Style (8th edition)

  • Zaidi, Nikki. "Hidden Variance in Multiple Mini-Interview Scores." Doctoral dissertation, University of Cincinnati, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427797882

    Chicago Manual of Style (17th edition)

ucin1427797882
688
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This open access ETD is published by University of Cincinnati and OhioLINK.