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

Kuan Yu JIN, Wen Chung WANG

Research output: Contribution to conferencePapers

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
EventNational Council on Measurement in Education 2016 Annual Meeting: Foundations and frontiers: Advancing educational measurement for research, policy, and practice - Washington, United States
Duration: 01 Apr 201611 Apr 2016

Conference

ConferenceNational Council on Measurement in Education 2016 Annual Meeting: Foundations and frontiers: Advancing educational measurement for research, policy, and practice
Abbreviated titleNCME2016
Country/TerritoryUnited States
CityWashington
Period01/04/1611/04/16

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.

Fingerprint

Dive into the research topics of 'The higher-order IRT model for global and local person dependence'. Together they form a unique fingerprint.