Evaluating the Douglas-Cohen IRT Goodness of Fit Measure With BIB Sampling of Items

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL Applied Psychological Measurement Pub Date : 2024-03-14 DOI:10.1177/01466216241238740
John R. Donoghue, Adrienne N. Sgammato
{"title":"Evaluating the Douglas-Cohen IRT Goodness of Fit Measure With BIB Sampling of Items","authors":"John R. Donoghue, Adrienne N. Sgammato","doi":"10.1177/01466216241238740","DOIUrl":null,"url":null,"abstract":"Methods to detect item response theory (IRT) item-level misfit are typically derived assuming fixed test forms. However, IRT is also employed with more complicated test designs, such as the balanced incomplete block (BIB) design used in large-scale educational assessments. This study investigates two modifications of Douglas and Cohen’s 2001 nonparametric method of assessing item misfit, based on A) using block total score and B) pooling booklet level scores for analyzing BIB data. Block-level scores showed extreme inflation of Type I error for short blocks containing 5 or 10 items. The pooled booklet method yielded Type I error rates close to nominal [Formula: see text] in most conditions and had power to detect misfitting items. The study also found that the Douglas and Cohen procedure is only slightly affected by the presence of other misfitting items in the block. The pooled booklet method is recommended for practical applications of Douglas and Cohen’s method with BIB data.","PeriodicalId":48300,"journal":{"name":"Applied Psychological Measurement","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Psychological Measurement","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/01466216241238740","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PSYCHOLOGY, MATHEMATICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Methods to detect item response theory (IRT) item-level misfit are typically derived assuming fixed test forms. However, IRT is also employed with more complicated test designs, such as the balanced incomplete block (BIB) design used in large-scale educational assessments. This study investigates two modifications of Douglas and Cohen’s 2001 nonparametric method of assessing item misfit, based on A) using block total score and B) pooling booklet level scores for analyzing BIB data. Block-level scores showed extreme inflation of Type I error for short blocks containing 5 or 10 items. The pooled booklet method yielded Type I error rates close to nominal [Formula: see text] in most conditions and had power to detect misfitting items. The study also found that the Douglas and Cohen procedure is only slightly affected by the presence of other misfitting items in the block. The pooled booklet method is recommended for practical applications of Douglas and Cohen’s method with BIB data.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用 BIB 项目抽样评估道格拉斯-科恩 IRT 拟合度量法
检测项目反应理论(IRT)项目级误差的方法通常是在假定测试形式固定的情况下得出的。然而,IRT 也适用于更复杂的测验设计,如大规模教育评估中使用的平衡不完全区组(BIB)设计。本研究调查了 Douglas 和 Cohen 2001 年评估项目不匹配度的非参数方法的两种修改方案,分别基于 A) 使用组块总分和 B) 汇总册级分数来分析 BIB 数据。对于包含 5 或 10 个项目的短块,块级得分显示出 I 类误差的极度膨胀。在大多数情况下,汇总的小册子方法产生的 I 类误差率接近名义误差率[公式:见正文],并且有能力检测出不匹配的项目。研究还发现,Douglas 和 Cohen 程序只会受到区块中存在其他不匹配项目的轻微影响。建议在实际应用道格拉斯和科恩的方法处理 BIB 数据时,采用集合小册子法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
期刊最新文献
Item Response Modeling of Clinical Instruments With Filter Questions: Disentangling Symptom Presence and Severity. A Note on Standard Errors for Multidimensional Two-Parameter Logistic Models Using Gaussian Variational Estimation Measurement Invariance Testing Works Accommodating and Extending Various Models for Special Effects Within the Generalized Partially Confirmatory Factor Analysis Framework Investigating Directional Invariance in an Item Response Tree Model for Extreme Response Style and Trait-Based Unfolding Responses
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1