{"title":"使用外部摘要信息的经验似然","authors":"Lyu Ni, Junchao Shao, Jinyi Wang, Lei Wang","doi":"10.5705/ss.202023.0056","DOIUrl":null,"url":null,"abstract":": Statistical analysis in modern scientific research nowadays has opportunities to utilize external summary information from similar studies to gain efficiency. However, the population generating data for current study, referred to as internal population, is typically different from the external population for summary information, although they share some common characteristics that make efficiency improvement possible. The existing population heterogeneity is a challenging issue especially when we have only summary statistics but not individual-level external data. In this paper, we apply an empirical likelihood approach to estimating internal population distribution, with external summary information utilized as constraints for efficiency gain under population heterogeneity. We show that our approach produces an asymptotically more efficient estimator of internal population distribution compared with the customary empirical likelihood without using any external information, under the condition that the external information is based on a dataset with size larger than that","PeriodicalId":49478,"journal":{"name":"Statistica Sinica","volume":"1 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Empirical Likelihood Using External Summary Information\",\"authors\":\"Lyu Ni, Junchao Shao, Jinyi Wang, Lei Wang\",\"doi\":\"10.5705/ss.202023.0056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Statistical analysis in modern scientific research nowadays has opportunities to utilize external summary information from similar studies to gain efficiency. However, the population generating data for current study, referred to as internal population, is typically different from the external population for summary information, although they share some common characteristics that make efficiency improvement possible. The existing population heterogeneity is a challenging issue especially when we have only summary statistics but not individual-level external data. In this paper, we apply an empirical likelihood approach to estimating internal population distribution, with external summary information utilized as constraints for efficiency gain under population heterogeneity. We show that our approach produces an asymptotically more efficient estimator of internal population distribution compared with the customary empirical likelihood without using any external information, under the condition that the external information is based on a dataset with size larger than that\",\"PeriodicalId\":49478,\"journal\":{\"name\":\"Statistica Sinica\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistica Sinica\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.5705/ss.202023.0056\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistica Sinica","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.5705/ss.202023.0056","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Empirical Likelihood Using External Summary Information
: Statistical analysis in modern scientific research nowadays has opportunities to utilize external summary information from similar studies to gain efficiency. However, the population generating data for current study, referred to as internal population, is typically different from the external population for summary information, although they share some common characteristics that make efficiency improvement possible. The existing population heterogeneity is a challenging issue especially when we have only summary statistics but not individual-level external data. In this paper, we apply an empirical likelihood approach to estimating internal population distribution, with external summary information utilized as constraints for efficiency gain under population heterogeneity. We show that our approach produces an asymptotically more efficient estimator of internal population distribution compared with the customary empirical likelihood without using any external information, under the condition that the external information is based on a dataset with size larger than that
期刊介绍:
Statistica Sinica aims to meet the needs of statisticians in a rapidly changing world. It provides a forum for the publication of innovative work of high quality in all areas of statistics, including theory, methodology and applications. The journal encourages the development and principled use of statistical methodology that is relevant for society, science and technology.