Simulation for education and training in health-care professions has been widely applied. However, its value as an assessment tool for competence is not fully known. Logistical barriers of simulation-based assessments have led some health-care organizations to utilize computer-based case simulations (CCSs) for assessment. This article provides a review of the literature on the identification of psychometrically sound, CCS instruments designed to measure decision-making competence in health-care professionals. CINAHL, MEDLINE, and Ovid databases identified 84 potentially relevant articles published between January 2000 and May 2017. A total of 12 articles met criteria for inclusion in this review. Findings of these 12 articles indicate that summative assessment in health care using CCSs in the form of clinical scenarios is utilized to assess higher order performance aspects of competence in the form of decision-making. Psychometric strength was validated in eight articles and supported by four replication studies. Two of the eight articles reported evidence of construct validity and support the need for evidence based on a theoretical framework. This literature review offers implications for further research on the use of CCS tools as a method for assessment of competence in health-care professionals and the need for psychometric evidence to support it.
It is known that the Rasch model is a special two‐level hierarchical generalized linear model (HGLM). This article demonstrates that the many‐faceted Rasch model (MFRM) is also a special case of the two‐level HGLM, with a random intercept representing examinee ability on a test, and fixed effects for the test items, judges, and possibly other facets. This perspective suggests useful modeling extensions of the MFRM. For example, in the HGLM framework it is possible to model random effects for items and judges in order to assess their stability across examinees. The MFRM can also be extended so that item difficulty and judge severity are modeled as functions of examinee characteristics (covariates), for the purposes of detecting differential item functioning and differential rater functioning. Practical illustrations of the HGLM are presented through the analysis of simulated and real judge‐mediated data sets involving ordinal responses.
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