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Raykov, Tenko – Measurement: Interdisciplinary Research and Perspectives, 2023
This software review discusses the capabilities of Stata to conduct item response theory modeling. The commands needed for fitting the popular one-, two-, and three-parameter logistic models are initially discussed. The procedure for testing the discrimination parameter equality in the one-parameter model is then outlined. The commands for fitting…
Descriptors: Item Response Theory, Models, Comparative Analysis, Item Analysis
Peabody, Michael R. – Measurement: Interdisciplinary Research and Perspectives, 2023
Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…
Descriptors: Programming Languages, Algorithms, Heuristics, Mathematical Models
Rupp, André A.; van Rijn, Peter W. – Measurement: Interdisciplinary Research and Perspectives, 2018
We review the GIDNA and CDM packages in R for fitting cognitive diagnosis/diagnostic classification models. We first provide a summary of their core capabilities and then use both simulated and real data to compare their functionalities in practice. We found that the most relevant routines in the two packages appear to be more similar than…
Descriptors: Educational Assessment, Cognitive Measurement, Measurement, Computer Software
Humphry, Stephen M. – Measurement: Interdisciplinary Research and Perspectives, 2011
The purpose of this article is to examine the role of the unit in physics in order to clarify the role of the unit in psychometrics. Based on this examination, metrological conventions are used to formulate the relationship between discrimination and the unit of a scale in item response theory. Seminal literature in two lines of item response…
Descriptors: Simulation, Social Sciences, Physics, Measures (Individuals)