Cited by 32Innovations in Medical EducationPsychometric Methodologies and TestingMedical Education and Admissions

The misinterpretation of the standard error of measurement in medical education: A primer on the problems, pitfalls and peculiarities of the three different standard errors of measurement

McManus, I. C.·2012·Medical Teacher

Abstract

Background In high-stakes assessments in medical education, such as final undergraduate examinations and postgraduate assessments, an attempt is frequently made to set confidence limits on the probable true score of a candidate. Typically, this is carried out using what is referred to as the standard error of measurement (SEM). However, it is often the case that the wrong formula is applied, there actually being three different formulae for use in different situations. Aims To explain and clarify the calculation of the SEM, and differentiate three separate standard errors, which here are called the standard error of measurement (SEmeas), the standard error of estimation (SEest) and the standard error of prediction (SEpred). Results Most accounts describe the calculation of SEmeas. For most purposes, though, what is required is the standard error of estimation (SEest), which has to be applied not to a candidate's actual score but to their estimated true score after taking into account the regression to the mean that occurs due to the unreliability of an assessment. A third formula, the standard error of prediction (SEpred) is less commonly used in medical education, but is useful in situations such as counselling, where one needs to predict a future actual score on an examination from a previous actual score on the same examination. Conclusions The various formulae can produce predictions that differ quite substantially, particularly when reliability is not particularly high,…

Integrity signals

Registry

Crossref · 10.3109/0142159x.2012.670318

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

  • The abstract notions of standard errors and associated uncertainty intervals are repeatedly associated with interpretation problems in clinical practitioners.

    “This topic is particularly relevant, given that the abstract notions of standard errors and associated uncertainty intervals are repeatedly associated with interpretation problems in this population (McManus, 2012).”
  • Measurement uncertainty is generally communicated in ways that can be difficult to understand for clinical practitioners, even for people who have received rigorous training.

    “This uncertainty is generally communicated in ways that can be difficult to understand for clinical practitioners.”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
McManus, I. C.
Affiliations
University College London (GB)
Corresponding author
McManus, I. C.
Venue
Medical Teacher
Published
2012-04-18
Volume
34
Issue
7
Pages
569-576
ISSN
  • 0142-159X (ISSN-L)
  • 1466-187X
OpenAlex
W2055475246
Cited by
32
References
1
Citations by year
2026: 3 · 2025: 2 · 2024: 2 · 2023: 5 · 2022: 3 · 2021: 7 · 2020: 1 · 2019: 3 · 2018: 1 · 2017: 1 · 2016: 2 · 2015: 2
FWCI
0.62
Type
journal article
Language
en
Open access
closed
Locations
  • Medical Teacher (publishedVersion)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Funders
University College London
Topics
  • 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
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Medical Education and Admissions
Keywords
standard error of measurement, standard error of estimation, standard error of prediction, high-stakes testing, medical education assessment, test reliability, regression to the mean, true score estimation, confidence limits, postgraduate assessment
MeSH terms
Education, Medical, Educational Measurement, United Kingdom, Humans, Reproducibility of Results, Models, Statistical

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