{"title":"Confidence Intervals for the Risk Difference Between Secondary and Primary Infection Based on the Method of Variance Estimates Recovery.","authors":"Chao Chen, Yuanzhen Li, Qitong Wei, Zhigang Huang, Yanting Chen","doi":"10.1002/pst.2458","DOIUrl":null,"url":null,"abstract":"<p><p>The risk difference (RD) between the secondary infection, given the primary infection, and the primary infection can be a useful measure of the change in the infection rates of the primary infection and the secondary infection. It plays an important role in pharmacology and epidemiology. The method of variance estimate recovery (MOVER) is used to construct confidence intervals (CIs) for the RD. Seven types of CIs for binomial proportion are introduced to obtain MOVER-based CIs for the RD. The simulation studies show that the Agresti-Coull CI, score method incorporating continuity correction CI, Clopper Pearson CI, and Bayesian credibility CI are conservative. The Jeffreys CI, Wilson score CI, and Arcsin CI draw a satisfactory performance; they are suitable for various practical application scenarios as they can provide accurate and reliable results. To illustrate that the recommended CIs are competitive or even better than other methods, three real datasets were used.</p>","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmaceutical Statistics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/pst.2458","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
The risk difference (RD) between the secondary infection, given the primary infection, and the primary infection can be a useful measure of the change in the infection rates of the primary infection and the secondary infection. It plays an important role in pharmacology and epidemiology. The method of variance estimate recovery (MOVER) is used to construct confidence intervals (CIs) for the RD. Seven types of CIs for binomial proportion are introduced to obtain MOVER-based CIs for the RD. The simulation studies show that the Agresti-Coull CI, score method incorporating continuity correction CI, Clopper Pearson CI, and Bayesian credibility CI are conservative. The Jeffreys CI, Wilson score CI, and Arcsin CI draw a satisfactory performance; they are suitable for various practical application scenarios as they can provide accurate and reliable results. To illustrate that the recommended CIs are competitive or even better than other methods, three real datasets were used.
期刊介绍:
Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics.
The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.