SIBTEST和交叉SIBTEST的多群推广

IF 1.1 4区教育学 Q3 EDUCATION & EDUCATIONAL RESEARCH

Applied Measurement in Education Pub Date : 2023-04-03 DOI:10.1080/08957347.2023.2201703

R. P. Chalmers, Guoguo Zheng

{"title":"SIBTEST和交叉SIBTEST的多群推广","authors":"R. P. Chalmers, Guoguo Zheng","doi":"10.1080/08957347.2023.2201703","DOIUrl":null,"url":null,"abstract":"ABSTRACT This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To investigate the Type I error and power behavior of these generalizations, a Monte Carlo simulation study was then explored. Results indicated that the proposed generalizations are reasonably effective at recovering their respective population parameter definitions, maintain optimal Type I error control, have suitable power to detect uniform and non-uniform DIF, and in shorter tests are competitive with the generalized logistic regression and generalized Mantel–Haenszel tests for DIF.","PeriodicalId":51609,"journal":{"name":"Applied Measurement in Education","volume":"36 1","pages":"171 - 191"},"PeriodicalIF":1.1000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Group Generalizations of SIBTEST and Crossing-SIBTEST\",\"authors\":\"R. P. Chalmers, Guoguo Zheng\",\"doi\":\"10.1080/08957347.2023.2201703\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To investigate the Type I error and power behavior of these generalizations, a Monte Carlo simulation study was then explored. Results indicated that the proposed generalizations are reasonably effective at recovering their respective population parameter definitions, maintain optimal Type I error control, have suitable power to detect uniform and non-uniform DIF, and in shorter tests are competitive with the generalized logistic regression and generalized Mantel–Haenszel tests for DIF.\",\"PeriodicalId\":51609,\"journal\":{\"name\":\"Applied Measurement in Education\",\"volume\":\"36 1\",\"pages\":\"171 - 191\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Measurement in Education\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://doi.org/10.1080/08957347.2023.2201703\",\"RegionNum\":4,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Measurement in Education","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1080/08957347.2023.2201703","RegionNum":4,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}

引用次数: 0

摘要

摘要本文对涉及两组以上的差异项目功能（DIF）调查的SIBTEST和交叉SIBTEST统计进行了概括。在回顾了这些统计数据的原始两组设置后，提出了一组支持DIF联合测试的对比矩阵的多组推广。为了研究这些推广的I型误差和幂行为，随后进行了蒙特卡洛模拟研究。结果表明，所提出的推广在恢复各自的总体参数定义方面相当有效，保持了最优的I型误差控制，具有检测均匀和非均匀DIF的适当能力，并且在较短的测试中与DIF的广义逻辑回归和广义Mantel–Haenszel测试具有竞争力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Multi-Group Generalizations of SIBTEST and Crossing-SIBTEST

ABSTRACT This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To investigate the Type I error and power behavior of these generalizations, a Monte Carlo simulation study was then explored. Results indicated that the proposed generalizations are reasonably effective at recovering their respective population parameter definitions, maintain optimal Type I error control, have suitable power to detect uniform and non-uniform DIF, and in shorter tests are competitive with the generalized logistic regression and generalized Mantel–Haenszel tests for DIF.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Applied Measurement in Education Multiple-

CiteScore

2.50

自引率

13.30%

发文量

期刊介绍： Because interaction between the domains of research and application is critical to the evaluation and improvement of new educational measurement practices, Applied Measurement in Education" prime objective is to improve communication between academicians and practitioners. To help bridge the gap between theory and practice, articles in this journal describe original research studies, innovative strategies for solving educational measurement problems, and integrative reviews of current approaches to contemporary measurement issues. Peer Review Policy: All review papers in this journal have undergone editorial screening and peer review.