Correction to “Expanding the Lognormal Response Time Model Using Profile Similarity Metrics to Improve the Detection of Anomalous Testing Behavior”

IF 1.4 4区心理学 Q3 PSYCHOLOGY, APPLIED Journal of Educational Measurement Pub Date : 2024-10-23 DOI:10.1111/jedm.12418

引用次数: 0

Abstract

Hurtz, G.M., & Mucino, R. (2024). Expanding the lognormal response time model using profile similarity metrics to improve the detection of anomalous testing behavior. Journal of Educational Measurement, 61, 458–485. https://doi.org/10.1111/jedm.12395

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来源期刊

Journal of Educational Measurement Multiple-

CiteScore

2.30

自引率

7.70%

发文量

期刊介绍： The Journal of Educational Measurement (JEM) publishes original measurement research, provides reviews of measurement publications, and reports on innovative measurement applications. The topics addressed will interest those concerned with the practice of measurement in field settings, as well as be of interest to measurement theorists. In addition to presenting new contributions to measurement theory and practice, JEM also serves as a vehicle for improving educational measurement applications in a variety of settings.

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Issue Information An Exploratory Study Using Innovative Graphical Network Analysis to Model Eye Movements in Spatial Reasoning Problem Solving Differences in Time Usage as a Competing Hypothesis for Observed Group Differences in Accuracy with an Application to Observed Gender Differences in PISA Data Correction to “Expanding the Lognormal Response Time Model Using Profile Similarity Metrics to Improve the Detection of Anomalous Testing Behavior” Subscores: A Practical Guide to Their Production and Consumption. Shelby Haberman, Sandip Sinharay, Richard Feinberg, and Howard Wainer. Cambridge, Cambridge University Press 2024, 176 pp. (paperback)