Challenges in Multilevel Modelling: Cross-Group Measurement Noninvariance and Measurement Errors. A Monte Carlo Simulation Study

IF 5.3 2区 社会学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS
Artur Pokropek, Tomasz Żółtak, Eldad Davidov, Bart Meuleman, Peter Schmidt
{"title":"Challenges in Multilevel Modelling: Cross-Group Measurement Noninvariance and Measurement Errors. A Monte Carlo Simulation Study","authors":"Artur Pokropek, Tomasz Żółtak, Eldad Davidov, Bart Meuleman, Peter Schmidt","doi":"10.1177/00491241251379459","DOIUrl":null,"url":null,"abstract":"Multilevel modelling (MM) is widely utilized in the social sciences, with over 20% of articles in leading sociological journals employing this technique. Despite its prevalence, few studies address whether the variables used in MM are invariant across groups or allow to construct reliable indicators. This study investigates the effects of both measurement noninvariance and random measurement error on MM using Monte Carlo simulations. Our findings reveal significant biases in MM results when random measurement errors are overlooked. Attaining high reliability in the indicators – above 0.94 – can mitigate these biases. While measurement noninvariance introduces bias in MM, its impact is smaller compared to that of the bias caused by unaddressed measurement error. Multilevel structural equation modelling (SEM), which controls for random measurement errors, performs effectively in complete measurement invariance (MI) scenarios. However, the absence of MI can create significant challenges. While multilevel SEM is a powerful analytical tool, it is not immune to the effects of MI assumption violations.","PeriodicalId":21849,"journal":{"name":"Sociological Methods & Research","volume":"100 1","pages":""},"PeriodicalIF":5.3000,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sociological Methods & Research","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/00491241251379459","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Multilevel modelling (MM) is widely utilized in the social sciences, with over 20% of articles in leading sociological journals employing this technique. Despite its prevalence, few studies address whether the variables used in MM are invariant across groups or allow to construct reliable indicators. This study investigates the effects of both measurement noninvariance and random measurement error on MM using Monte Carlo simulations. Our findings reveal significant biases in MM results when random measurement errors are overlooked. Attaining high reliability in the indicators – above 0.94 – can mitigate these biases. While measurement noninvariance introduces bias in MM, its impact is smaller compared to that of the bias caused by unaddressed measurement error. Multilevel structural equation modelling (SEM), which controls for random measurement errors, performs effectively in complete measurement invariance (MI) scenarios. However, the absence of MI can create significant challenges. While multilevel SEM is a powerful analytical tool, it is not immune to the effects of MI assumption violations.
多层次建模的挑战:跨组测量不变性和测量误差。蒙特卡罗模拟研究
多层次建模(MM)在社会科学中被广泛应用,超过20%的主要社会学期刊文章采用了这种技术。尽管它很流行,但很少有研究解决MM中使用的变量是否在群体中不变或允许构建可靠的指标。本研究利用蒙特卡罗模拟研究了测量不变性和随机测量误差对MM的影响。我们的研究结果显示,当随机测量误差被忽略时,MM结果显着偏差。在指标中获得高可靠性(高于0.94)可以减轻这些偏差。虽然测量不变性在MM中引入了偏差,但与未解决的测量误差引起的偏差相比,其影响较小。多层结构方程模型(SEM)能够有效地控制随机测量误差,在完全测量不变性(MI)情况下表现良好。然而,MI的缺失可能会带来重大挑战。虽然多层扫描电镜是一种强大的分析工具,但它也不能避免MI假设违反的影响。
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 求助全文
来源期刊
CiteScore
16.30
自引率
3.20%
发文量
40
期刊介绍: Sociological Methods & Research is a quarterly journal devoted to sociology as a cumulative empirical science. The objectives of SMR are multiple, but emphasis is placed on articles that advance the understanding of the field through systematic presentations that clarify methodological problems and assist in ordering the known facts in an area. Review articles will be published, particularly those that emphasize a critical analysis of the status of the arts, but original presentations that are broadly based and provide new research will also be published. Intrinsically, SMR is viewed as substantive journal but one that is highly focused on the assessment of the scientific status of sociology. The scope is broad and flexible, and authors are invited to correspond with the editors about the appropriateness of their articles.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书