Should candidate scores be adjusted for interviewer stringency or leniency in the multiple mini-interview?
Open accessAbstract
Medical Education 2010: 44 : 690–698 Context There are significant levels of variation in candidate multiple mini‐interview (MMI) scores caused by interviewer‐related factors. Multi‐facet Rasch modelling (MFRM) has the capability to both identify these sources of error and partially adjust for them within a measurement model that may be fairer to the candidate. Methods Using facets software, a variance components analysis estimated sources of measurement error that were comparable with those produced by generalisability theory. Fair average scores for the effects of the stringency/leniency of interviewers and question difficulty were calculated and adjusted rankings of candidates were modelled. Results The decisions of 207 interviewers had an acceptable fit to the MFRM model. For one candidate assessed by one interviewer on one MMI question, 19.1% of the variance reflected candidate ability, 8.9% reflected interviewer stringency/leniency, 5.1% reflected interviewer question‐specific stringency/leniency and 2.6% reflected question difficulty. If adjustments were made to candidates’ raw scores for interviewer stringency/leniency and question difficulty, 11.5% of candidates would see a significant change in their ranking for selection into the programme. Greater interviewer leniency was associated with the number of candidates interviewed. Conclusions Interviewers differ in their degree of stringency/leniency and this appears to be a stable characteristic. The MFRM provides a recommendable way of giving a candidate score which adjusts for the stringency/leniency of whichever interviewers the candidate sees and the difficulty of the questions the candidate is asked.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In Roberts et al. (2010), the decisions of 207 interviewers had an acceptable fit to the MFRM model.
“Decision of 207 interviewers had an acceptable fit to the MFRM model.”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (27) 2010
In Roberts et al. (2010), the reliability of separation index for stringency/leniency was 0.91.
“Reliability of separation index in terms of stringency/leniency gave a reliability of 0.91”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (27) 2010
In Roberts et al. (2010), the high reliability indicates that interviewers are meaningfully separated according to their levels of severity from lenient to stringent with a high degree of confidence.
“High reliability indicates that the interviewers are meaningfully separated according to their levels of severity from lenient to stringent with a high degree of confidence”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (27) 2010
In Roberts et al. (2010), interviewers were more variable than MMI questions, with the spread of interviewers nearly 3.5 times that of MMI questions.
“Interviewers are more variable than MMI questions and the spread of interviewers is nearly 3.5 times that of MMI questions.”
From Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review (2019) · cites this paper as Roberts C. et al., (27) 2010
Cites
The assessment of professional competence: Developments, research and practical implications
Van Der Vleuten, C. P. M. (1996) · Advances in Health Sciences Education · doi:10.1007/bf00596229 · Cited by 1,247 · see citing works
An admissions OSCE: the multiple mini-interview
Eva, K. W., Rosenfeld, J., Reiter, H. I., & Norman, G. R. (2004) · Medical Education · doi:10.1046/j.1365-2923.2004.01776.x · Cited by 617 · see citing works
Multiple mini-interviews predict clerkship and licensing examination performance
Reiter, H. I., Eva, K. W., Rosenfeld, J., & Norman, G. R. (2007) · Medical Education · doi:10.1111/j.1365-2929.2007.02709.x · Cited by 235 · see citing works
Experiences of the multiple mini-interview: a qualitative analysis
Kumar, K., Roberts, C., Rothnie, I., Du Fresne, C., & Walton, M. (2009) · Medical Education · doi:10.1111/j.1365-2923.2009.03291.x · Cited by 68 · see citing works
Self-citationRoberts, C., Zoanetti, N., & Rothnie, I. (2009) · Medical Education · doi:10.1111/j.1365-2923.2009.03292.x · Cited by 49 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Pau, A., Jeevaratnam, K., Chen, Y. S., Fall, A. A., Khoo, C., & Nadarajah, V. D. (2013) · Medical Teacher · doi:10.3109/0142159x.2013.829912 · Cited by 195 · see citing works
Rees, E. L., Hawarden, A. W., Dent, G., Hays, R., Bates, J., & Hassell, A. B. (2016) · Medical Teacher · doi:10.3109/0142159x.2016.1158799 · Cited by 139 · see citing works
Multiple mini-interviews: same concept, different approaches
Knorr, M., & Hissbach, J. (2014) · Medical Education · doi:10.1111/medu.12535 · Cited by 110 · see citing works
The multiple mini-interview in the UK context: 3 years of experience at Dundee
Dowell, J., Lynch, B., Till, H., Kumwenda, B., & Husbands, A. (2012) · Medical Teacher · doi:10.3109/0142159x.2012.652706 · Cited by 74 · see citing works
Multiple Mini Interview as an admission tool in higher education: Insights from a systematic review
Yusoff, M. S. B. (2019) · Journal of Taibah University Medical Sciences · doi:10.1016/j.jtumed.2019.03.006 · Cited by 57 · see citing works
“, (20) 2009 McMaster University, Canada Undergraduate N 1⁄4 34 Postgraduate N 1⁄4 22 Medical School Tests of the validity of the MMI selection process, comparing MMI scores with those achieved on a national high-stakes clinical skills examination Explore the stability of candidate performance and the extent to which s…”
MethodRoberts, C., Clark, T., Burgess, A., Frommer, M., Grant, M., & Mossman, K. (2014) · BMC Medical Education · doi:10.1186/1472-6920-14-169 · Cited by 49 · see citing works
Self-citationHissbach, J. C., Sehner, S., Harendza, S., & Hampe, W. (2014) · BMC Medical Education · doi:10.1186/1472-6920-14-54 · Cited by 37 · see citing works
Improving student selection using multiple mini-interviews with multifaceted Rasch modeling
Till, H., Myford, C., & Dowell, J. (2013) · Academic Medicine · doi:10.1097/acm.0b013e31827c0c5d · Cited by 31 · see citing works
- Authors
- Roberts, C., Rothnie, I., Zoanetti, N., & Crossley, J.
- Affiliations
- The University of Sydney (AU)
- The University of Melbourne (AU)
- University of Sheffield (GB)
- Corresponding author
- Roberts, Chris
- Venue
- Medical Education
- Publisher
- Wiley
- Published
- 2010-06-15
- Volume
- 44
- Issue
- 7
- Pages
- 690-698
- ISSN
- 0308-0110 (ISSN-L)
- 1365-2923
- OpenAlex
- W1526475988
- Cited by
- 59
- References
- 5
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 4 · 2023: 4 · 2022: 3 · 2021: 4 · 2020: 5 · 2019: 5 · 2018: 4 · 2017: 4 · 2016: 7 · 2015: 2 · 2014: 3 · 2013: 3 · 2012: 2
- FWCI
- 2.87
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Medical Education (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical Education and Admissions
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- multiple mini-interviews, score adjustment, measurement error, question difficulty, candidate ranking, medical school admissions
- MeSH terms
- Clinical Competence, Communication, Educational Measurement, Faculty, Medical, Humans, Interviews as Topic, Psychometrics, School Admission Criteria, Observer Variation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review