{"title":"灵活控制错误发现比例的中位数","authors":"Jesse Hemerik, Aldo Solari, Jelle J Goeman","doi":"10.1093/biomet/asae018","DOIUrl":null,"url":null,"abstract":"We introduce a multiple testing procedure that controls the median of the proportion of false discoveries in a flexible way. The procedure only requires a vector of p-values as input and is comparable to the Benjamini–Hochberg method, which controls the mean of the proportion of false discoveries. Our method allows free choice of one or several values of alpha after seeing the data, unlike the Benjamini–Hochberg procedure, which can be very anti-conservative when alpha is chosen post hoc. We prove these claims and illustrate them with simulations. Our procedure is inspired by a popular estimator of the total number of true hypotheses. We adapt this estimator to provide simultaneously median unbiased estimators of the proportion of false discoveries, valid for finite samples. This simultaneity allows for the claimed flexibility. Our approach does not assume independence. The time complexity of our method is linear in the number of hypotheses, after sorting the p-values.","PeriodicalId":9001,"journal":{"name":"Biometrika","volume":"309 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Flexible control of the median of the false discovery proportion\",\"authors\":\"Jesse Hemerik, Aldo Solari, Jelle J Goeman\",\"doi\":\"10.1093/biomet/asae018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a multiple testing procedure that controls the median of the proportion of false discoveries in a flexible way. The procedure only requires a vector of p-values as input and is comparable to the Benjamini–Hochberg method, which controls the mean of the proportion of false discoveries. Our method allows free choice of one or several values of alpha after seeing the data, unlike the Benjamini–Hochberg procedure, which can be very anti-conservative when alpha is chosen post hoc. We prove these claims and illustrate them with simulations. Our procedure is inspired by a popular estimator of the total number of true hypotheses. We adapt this estimator to provide simultaneously median unbiased estimators of the proportion of false discoveries, valid for finite samples. This simultaneity allows for the claimed flexibility. Our approach does not assume independence. The time complexity of our method is linear in the number of hypotheses, after sorting the p-values.\",\"PeriodicalId\":9001,\"journal\":{\"name\":\"Biometrika\",\"volume\":\"309 1\",\"pages\":\"\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biometrika\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1093/biomet/asae018\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biometrika","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1093/biomet/asae018","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
我们介绍了一种多重检验程序,它能以灵活的方式控制错误发现比例的中位数。该程序只需要一个 p 值向量作为输入,与控制错误发现比例均值的本杰明-霍奇伯格方法具有可比性。我们的方法允许在看到数据后自由选择一个或多个 alpha 值,这与 Benjamini-Hochberg 程序不同,后者在事后选择 alpha 值时可能非常不保守。我们证明了这些说法,并通过模拟进行了说明。我们的程序受到一个流行的真实假设总数估计器的启发。我们对这个估计器进行了调整,以同时提供对有限样本有效的错误发现比例的中值无偏估计器。这种同时性使我们获得了所宣称的灵活性。我们的方法不假定独立性。在对 p 值进行排序后,我们方法的时间复杂度与假设数量成线性关系。
Flexible control of the median of the false discovery proportion
We introduce a multiple testing procedure that controls the median of the proportion of false discoveries in a flexible way. The procedure only requires a vector of p-values as input and is comparable to the Benjamini–Hochberg method, which controls the mean of the proportion of false discoveries. Our method allows free choice of one or several values of alpha after seeing the data, unlike the Benjamini–Hochberg procedure, which can be very anti-conservative when alpha is chosen post hoc. We prove these claims and illustrate them with simulations. Our procedure is inspired by a popular estimator of the total number of true hypotheses. We adapt this estimator to provide simultaneously median unbiased estimators of the proportion of false discoveries, valid for finite samples. This simultaneity allows for the claimed flexibility. Our approach does not assume independence. The time complexity of our method is linear in the number of hypotheses, after sorting the p-values.
期刊介绍:
Biometrika is primarily a journal of statistics in which emphasis is placed on papers containing original theoretical contributions of direct or potential value in applications. From time to time, papers in bordering fields are also published.