{"title":"二项早停时间","authors":"N. Mulgan","doi":"10.1080/07474946.2021.2010409","DOIUrl":null,"url":null,"abstract":"Abstract Sequential analysis for the purposes of possibly stopping a trial early is important whenever a result must be obtained as quickly as possible for public health, economic, or other reasons. A dominant research stream since the middle of the 20th century has been the challenge of generalizing Wald’s sequential probability ratio test (SPRT) to include composite alternative hypotheses. This article offers an alternative for a binomial distribution by constructing a single-parameter family of triangular rejection regions for the null hypothesis using a generation function argument in the two-dimensional space of successes versus failures. The result is algebraically equivalent to one line of the SPRT with unit power and with the second value of the binomial parameter as the undetermined parameter. Rounding then discretizes the line to the grid of two-dimensional integers and classical results for arbitrary stopping conditions are used to give expressions for the estimator, of the binomial parameter and its variance The choice can be made by the practitioner in terms of their appetite for risk or more formally via a power analysis. An example is given of an ecological study where a quick binary decision was required and this desire had to be weighed against robustness of the results.","PeriodicalId":48879,"journal":{"name":"Sequential Analysis-Design Methods and Applications","volume":"40 1","pages":"501 - 517"},"PeriodicalIF":0.6000,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Binomial early stopping times\",\"authors\":\"N. Mulgan\",\"doi\":\"10.1080/07474946.2021.2010409\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Sequential analysis for the purposes of possibly stopping a trial early is important whenever a result must be obtained as quickly as possible for public health, economic, or other reasons. A dominant research stream since the middle of the 20th century has been the challenge of generalizing Wald’s sequential probability ratio test (SPRT) to include composite alternative hypotheses. This article offers an alternative for a binomial distribution by constructing a single-parameter family of triangular rejection regions for the null hypothesis using a generation function argument in the two-dimensional space of successes versus failures. The result is algebraically equivalent to one line of the SPRT with unit power and with the second value of the binomial parameter as the undetermined parameter. Rounding then discretizes the line to the grid of two-dimensional integers and classical results for arbitrary stopping conditions are used to give expressions for the estimator, of the binomial parameter and its variance The choice can be made by the practitioner in terms of their appetite for risk or more formally via a power analysis. An example is given of an ecological study where a quick binary decision was required and this desire had to be weighed against robustness of the results.\",\"PeriodicalId\":48879,\"journal\":{\"name\":\"Sequential Analysis-Design Methods and Applications\",\"volume\":\"40 1\",\"pages\":\"501 - 517\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2021-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sequential Analysis-Design Methods and Applications\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/07474946.2021.2010409\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sequential Analysis-Design Methods and Applications","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/07474946.2021.2010409","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Abstract Sequential analysis for the purposes of possibly stopping a trial early is important whenever a result must be obtained as quickly as possible for public health, economic, or other reasons. A dominant research stream since the middle of the 20th century has been the challenge of generalizing Wald’s sequential probability ratio test (SPRT) to include composite alternative hypotheses. This article offers an alternative for a binomial distribution by constructing a single-parameter family of triangular rejection regions for the null hypothesis using a generation function argument in the two-dimensional space of successes versus failures. The result is algebraically equivalent to one line of the SPRT with unit power and with the second value of the binomial parameter as the undetermined parameter. Rounding then discretizes the line to the grid of two-dimensional integers and classical results for arbitrary stopping conditions are used to give expressions for the estimator, of the binomial parameter and its variance The choice can be made by the practitioner in terms of their appetite for risk or more formally via a power analysis. An example is given of an ecological study where a quick binary decision was required and this desire had to be weighed against robustness of the results.
期刊介绍:
The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches.
Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.