{"title":"基于p值调整meta分析发表偏倚的实用方法","authors":"N. Matsuoka, Chihiro Hasegawa, C. Hamada","doi":"10.5691/JJB.28.19","DOIUrl":null,"url":null,"abstract":"Meta-analysis of randomized controlled trials is a widely used study methodology and it is considered to provide the highest level of evidence. The results of such analysis, however, by the nature of this methodology, may be affected by a very serious bias referred to as publication bias. Although the trim-and-fill method has been proposed as a means of adjusting for publication bias, it does not necessarily provide a suitable correction under realistic circumstances. This article proposes a new method to correct for publication bias based on p-value and evaluates the performance of this method by means of simulations. It is shown that the performance of the proposed method is superior to that of the trim-and-fill method under realistic situations.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Practical Method Adjusting for Publication Bias in Meta-analysis Based on p-value\",\"authors\":\"N. Matsuoka, Chihiro Hasegawa, C. Hamada\",\"doi\":\"10.5691/JJB.28.19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Meta-analysis of randomized controlled trials is a widely used study methodology and it is considered to provide the highest level of evidence. The results of such analysis, however, by the nature of this methodology, may be affected by a very serious bias referred to as publication bias. Although the trim-and-fill method has been proposed as a means of adjusting for publication bias, it does not necessarily provide a suitable correction under realistic circumstances. This article proposes a new method to correct for publication bias based on p-value and evaluates the performance of this method by means of simulations. It is shown that the performance of the proposed method is superior to that of the trim-and-fill method under realistic situations.\",\"PeriodicalId\":365545,\"journal\":{\"name\":\"Japanese journal of biometrics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Japanese journal of biometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5691/JJB.28.19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Japanese journal of biometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5691/JJB.28.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Practical Method Adjusting for Publication Bias in Meta-analysis Based on p-value
Meta-analysis of randomized controlled trials is a widely used study methodology and it is considered to provide the highest level of evidence. The results of such analysis, however, by the nature of this methodology, may be affected by a very serious bias referred to as publication bias. Although the trim-and-fill method has been proposed as a means of adjusting for publication bias, it does not necessarily provide a suitable correction under realistic circumstances. This article proposes a new method to correct for publication bias based on p-value and evaluates the performance of this method by means of simulations. It is shown that the performance of the proposed method is superior to that of the trim-and-fill method under realistic situations.