The higher-order IRT model for global and local person dependence

Kuan Yu JIN, Wen Chung WANG

Research output: Contribution to conference › Papers

Abstract

Persons from the same clusters may behave more similarly than those from different clusters. In this study, we proposed a higher-order partial credit model for person clustering to quantify global and local person dependence for clustered samples in multiple tests. Simulations studies supported good parameter recovery of the new model.
Original languageEnglish
Publication statusPublished - Apr 2016

Citation

Jin, K.-Y., & Wang, W.-C. (2016, April). The higher-order IRT model for global and local person dependence. Paper presented at the National Council on Measurement in Education (NCME) 2016 Annual Meeting: Foundations and frontiers: Advancing educational measurement for research, policy, and practice, DC Downtown Hotel, Washington, DC.

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