{"title":"不同分层抽样方案下基于核的比值比估计","authors":"Abbas Eftekharian, H. Samawi, Haresh Rochani","doi":"10.19139/soic-2310-5070-1425","DOIUrl":null,"url":null,"abstract":" The kernel-based estimator of Cochran Mantel-Haenszel odds ratio based on stratified simple and ranked set sampling is proposed. The expectation and variance of the estimator are analytically obtained. Using a simulation study, the estimator based on stratified ranked set sampling is more efficient than its counterpart based on stratified simple random sampling. Finally, the estimator's performance is investigated by using base deficit data.","PeriodicalId":131002,"journal":{"name":"Statistics, Optimization & Information Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On Kernel-Based Estimator of Odds Ratio Using Different Stratified Sampling Schemes\",\"authors\":\"Abbas Eftekharian, H. Samawi, Haresh Rochani\",\"doi\":\"10.19139/soic-2310-5070-1425\",\"DOIUrl\":null,\"url\":null,\"abstract\":\" The kernel-based estimator of Cochran Mantel-Haenszel odds ratio based on stratified simple and ranked set sampling is proposed. The expectation and variance of the estimator are analytically obtained. Using a simulation study, the estimator based on stratified ranked set sampling is more efficient than its counterpart based on stratified simple random sampling. Finally, the estimator's performance is investigated by using base deficit data.\",\"PeriodicalId\":131002,\"journal\":{\"name\":\"Statistics, Optimization & Information Computing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics, Optimization & Information Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.19139/soic-2310-5070-1425\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics, Optimization & Information Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19139/soic-2310-5070-1425","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On Kernel-Based Estimator of Odds Ratio Using Different Stratified Sampling Schemes
The kernel-based estimator of Cochran Mantel-Haenszel odds ratio based on stratified simple and ranked set sampling is proposed. The expectation and variance of the estimator are analytically obtained. Using a simulation study, the estimator based on stratified ranked set sampling is more efficient than its counterpart based on stratified simple random sampling. Finally, the estimator's performance is investigated by using base deficit data.
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