{"title":"基于irt的回应风格模型及相关方法:回顾与评论。","authors":"Daniel M Bolt, Lionel Meng","doi":"10.1111/bmsp.70006","DOIUrl":null,"url":null,"abstract":"<p><p>We provide a review and commentary on recent methodological research related to item response theory (IRT) modelling of response styles in psychological measurement. Our review describes the different categories of IRT models that have been proposed, their associated assumptions and extensions, and the varying purposes they can serve. Our review also seeks to highlight some of the fundamental challenges shared across models in the study and statistical control of response style behaviour. We conclude with some thoughts regarding future directions, including the potential uses of response style models for sensitivity analysis and informed survey design and administration.</p>","PeriodicalId":55322,"journal":{"name":"British Journal of Mathematical & Statistical Psychology","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IRT-based response style models and related methodology: Review and commentary.\",\"authors\":\"Daniel M Bolt, Lionel Meng\",\"doi\":\"10.1111/bmsp.70006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We provide a review and commentary on recent methodological research related to item response theory (IRT) modelling of response styles in psychological measurement. Our review describes the different categories of IRT models that have been proposed, their associated assumptions and extensions, and the varying purposes they can serve. Our review also seeks to highlight some of the fundamental challenges shared across models in the study and statistical control of response style behaviour. We conclude with some thoughts regarding future directions, including the potential uses of response style models for sensitivity analysis and informed survey design and administration.</p>\",\"PeriodicalId\":55322,\"journal\":{\"name\":\"British Journal of Mathematical & Statistical Psychology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2025-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"British Journal of Mathematical & Statistical Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1111/bmsp.70006\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"British Journal of Mathematical & Statistical Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1111/bmsp.70006","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
IRT-based response style models and related methodology: Review and commentary.
We provide a review and commentary on recent methodological research related to item response theory (IRT) modelling of response styles in psychological measurement. Our review describes the different categories of IRT models that have been proposed, their associated assumptions and extensions, and the varying purposes they can serve. Our review also seeks to highlight some of the fundamental challenges shared across models in the study and statistical control of response style behaviour. We conclude with some thoughts regarding future directions, including the potential uses of response style models for sensitivity analysis and informed survey design and administration.
期刊介绍:
The British Journal of Mathematical and Statistical Psychology publishes articles relating to areas of psychology which have a greater mathematical or statistical aspect of their argument than is usually acceptable to other journals including:
• mathematical psychology
• statistics
• psychometrics
• decision making
• psychophysics
• classification
• relevant areas of mathematics, computing and computer software
These include articles that address substantitive psychological issues or that develop and extend techniques useful to psychologists. New models for psychological processes, new approaches to existing data, critiques of existing models and improved algorithms for estimating the parameters of a model are examples of articles which may be favoured.