{"title":"在小区域估计的样本分配中登记数据","authors":"Mauno Keto, Jussi Hakanen, Erkki Pahkinen","doi":"10.1080/08898480.2018.1437318","DOIUrl":null,"url":null,"abstract":"ABSTRACT The inadequate control of sample sizes in surveys using stratified sampling and area estimation may occur when the overall sample size is small or auxiliary information is insufficiently used. Very small sample sizes are possible for some areas. The proposed allocation based on multi-objective optimization uses a small-area model and estimation method and semi-collected empirical data annually collected empirical data. The assessment of its performance at the area and at the population levels is based on design-based sample simulations. Five previously developed allocations serve as references. The model-based estimator is more accurate than the design-based Horvitz–Thompson estimator and the model-assisted regression estimator. Two trade-off issues are between accuracy and bias and between the area- and the population-level qualities of estimates. If the survey uses model-based estimation, the sampling design should incorporate the underlying model and the estimation method.","PeriodicalId":49859,"journal":{"name":"Mathematical Population Studies","volume":"25 1","pages":"184 - 214"},"PeriodicalIF":1.4000,"publicationDate":"2018-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/08898480.2018.1437318","citationCount":"1","resultStr":"{\"title\":\"Register data in sample allocations for small-area estimation\",\"authors\":\"Mauno Keto, Jussi Hakanen, Erkki Pahkinen\",\"doi\":\"10.1080/08898480.2018.1437318\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT The inadequate control of sample sizes in surveys using stratified sampling and area estimation may occur when the overall sample size is small or auxiliary information is insufficiently used. Very small sample sizes are possible for some areas. The proposed allocation based on multi-objective optimization uses a small-area model and estimation method and semi-collected empirical data annually collected empirical data. The assessment of its performance at the area and at the population levels is based on design-based sample simulations. Five previously developed allocations serve as references. The model-based estimator is more accurate than the design-based Horvitz–Thompson estimator and the model-assisted regression estimator. Two trade-off issues are between accuracy and bias and between the area- and the population-level qualities of estimates. If the survey uses model-based estimation, the sampling design should incorporate the underlying model and the estimation method.\",\"PeriodicalId\":49859,\"journal\":{\"name\":\"Mathematical Population Studies\",\"volume\":\"25 1\",\"pages\":\"184 - 214\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2018-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/08898480.2018.1437318\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematical Population Studies\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1080/08898480.2018.1437318\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DEMOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Population Studies","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/08898480.2018.1437318","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DEMOGRAPHY","Score":null,"Total":0}
Register data in sample allocations for small-area estimation
ABSTRACT The inadequate control of sample sizes in surveys using stratified sampling and area estimation may occur when the overall sample size is small or auxiliary information is insufficiently used. Very small sample sizes are possible for some areas. The proposed allocation based on multi-objective optimization uses a small-area model and estimation method and semi-collected empirical data annually collected empirical data. The assessment of its performance at the area and at the population levels is based on design-based sample simulations. Five previously developed allocations serve as references. The model-based estimator is more accurate than the design-based Horvitz–Thompson estimator and the model-assisted regression estimator. Two trade-off issues are between accuracy and bias and between the area- and the population-level qualities of estimates. If the survey uses model-based estimation, the sampling design should incorporate the underlying model and the estimation method.
期刊介绍:
Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions.
The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.