
RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
Essays on Contemporary Psychometrics: Pages 163-180
This paper shows that using non-linear functions for equating and score transformations leads to consequences that are not commensurable with classical test theory (CTT). More specifically, a well-known theorem from calculus shows that the expected value of a non-linearly transformed variable does not equal the transformed expected value of this variable.
Teaching and Learning in Medicine: Volume 33 - Issue 4 - p 366-381
The purpose of this analysis is to describe these sources of evidence that can be used to evaluate the quality of generated items. The important role of medical expertise in the development and evaluation of the generated items is highlighted as a crucial requirement for producing validation evidence.
Psychometrika 83, 847–857 (2018)
Utilizing algorithms to generate items in educational and psychological testing is an active area of research for obvious reasons: Test items are predominantly written by humans, in most cases by content experts who represent a limited and potentially costly resource. Using algorithms instead has the appeal to provide an unlimited resource for this crucial part of assessment development.