{"title":"使用有限信息方法生成随机项目反应数据:评估模型复杂性的应用。","authors":"Yon Soo Suh, Wes Bonifay, Li Cai","doi":"10.1017/psy.2025.10017","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":54534,"journal":{"name":"Psychometrika","volume":" ","pages":"1-51"},"PeriodicalIF":2.9000,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Random Item Response Data Generation Using a Limited-Information Approach: Applications to Assessing Model Complexity.\",\"authors\":\"Yon Soo Suh, Wes Bonifay, Li Cai\",\"doi\":\"10.1017/psy.2025.10017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":54534,\"journal\":{\"name\":\"Psychometrika\",\"volume\":\" \",\"pages\":\"1-51\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Psychometrika\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1017/psy.2025.10017\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychometrika","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1017/psy.2025.10017","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
期刊介绍:
The journal Psychometrika is devoted to the advancement of theory and methodology for behavioral data in psychology, education and the social and behavioral sciences generally. Its coverage is offered in two sections: Theory and Methods (T& M), and Application Reviews and Case Studies (ARCS). T&M articles present original research and reviews on the development of quantitative models, statistical methods, and mathematical techniques for evaluating data from psychology, the social and behavioral sciences and related fields. Application Reviews can be integrative, drawing together disparate methodologies for applications, or comparative and evaluative, discussing advantages and disadvantages of one or more methodologies in applications. Case Studies highlight methodology that deepens understanding of substantive phenomena through more informative data analysis, or more elegant data description.