{"title":"是时候建设了:时间到事件数据的小面积估算方法","authors":"Nelson J.Y. Chua, Benjamin Y.B. Long","doi":"10.3233/sji-230075","DOIUrl":null,"url":null,"abstract":"There is an ever-present demand for statistical agencies to improve the timeliness, granularity and cost-efficiency of their official statistics. Our methodology for small area estimation using time-to-event data addresses these demands, as it utilises existing data sources to produce timely estimates at finer levels of geography. We illustrate this methodology with our application to the Australian Building Activity Survey, which has been successfully repurposed to obtain small area estimates of newly completed dwellings with associated uncertainty estimates. The methodology is widely applicable, and we discuss further subject areas where it can be introduced to improve value for users of official statistics.","PeriodicalId":55877,"journal":{"name":"Statistical Journal of the IAOS","volume":"92 1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"It’s time to build: A small area estimation methodology for time-to-event data\",\"authors\":\"Nelson J.Y. Chua, Benjamin Y.B. Long\",\"doi\":\"10.3233/sji-230075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is an ever-present demand for statistical agencies to improve the timeliness, granularity and cost-efficiency of their official statistics. Our methodology for small area estimation using time-to-event data addresses these demands, as it utilises existing data sources to produce timely estimates at finer levels of geography. We illustrate this methodology with our application to the Australian Building Activity Survey, which has been successfully repurposed to obtain small area estimates of newly completed dwellings with associated uncertainty estimates. The methodology is widely applicable, and we discuss further subject areas where it can be introduced to improve value for users of official statistics.\",\"PeriodicalId\":55877,\"journal\":{\"name\":\"Statistical Journal of the IAOS\",\"volume\":\"92 1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistical Journal of the IAOS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/sji-230075\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Journal of the IAOS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/sji-230075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Decision Sciences","Score":null,"Total":0}
It’s time to build: A small area estimation methodology for time-to-event data
There is an ever-present demand for statistical agencies to improve the timeliness, granularity and cost-efficiency of their official statistics. Our methodology for small area estimation using time-to-event data addresses these demands, as it utilises existing data sources to produce timely estimates at finer levels of geography. We illustrate this methodology with our application to the Australian Building Activity Survey, which has been successfully repurposed to obtain small area estimates of newly completed dwellings with associated uncertainty estimates. The methodology is widely applicable, and we discuss further subject areas where it can be introduced to improve value for users of official statistics.
期刊介绍:
This is the flagship journal of the International Association for Official Statistics and is expected to be widely circulated and subscribed to by individuals and institutions in all parts of the world. The main aim of the Journal is to support the IAOS mission by publishing articles to promote the understanding and advancement of official statistics and to foster the development of effective and efficient official statistical services on a global basis. Papers are expected to be of wide interest to readers. Such papers may or may not contain strictly original material. All papers are refereed.