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Reliability: on the reproducibility of assessment data
Author(s) -
Downing Steven M
Publication year - 2004
Publication title -
medical education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 138
eISSN - 1365-2923
pISSN - 0308-0110
DOI - 10.1111/j.1365-2929.2004.01932.x
Subject(s) - reliability (semiconductor) , inter rater reliability , consistency (knowledge bases) , context (archaeology) , computer science , reliability engineering , statistics , psychology , mathematics , artificial intelligence , rating scale , engineering , paleontology , power (physics) , physics , quantum mechanics , biology
Context All assessment data, like other scientific experimental data, must be reproducible in order to be meaningfully interpreted. Purpose The purpose of this paper is to discuss applications of reliability to the most common assessment methods in medical education. Typical methods of estimating reliability are discussed intuitively and non‐mathematically. Summary Reliability refers to the consistency of assessment outcomes. The exact type of consistency of greatest interest depends on the type of assessment, its purpose and the consequential use of the data. Written tests of cognitive achievement look to internal test consistency, using estimation methods derived from the test‐retest design. Rater‐based assessment data, such as ratings of clinical performance on the wards, require interrater consistency or agreement. Objective structured clinical examinations, simulated patient examinations and other performance‐type assessments generally require generalisability theory analysis to account for various sources of measurement error in complex designs and to estimate the consistency of the generalisations to a universe or domain of skills. Conclusions Reliability is a major source of validity evidence for assessments. Low reliability indicates that large variations in scores can be expected upon retesting. Inconsistent assessment scores are difficult or impossible to interpret meaningfully and thus reduce validity evidence. Reliability coefficients allow the quantification and estimation of the random errors of measurement in assessments, such that overall assessment can be improved.