{"title":"超越简单的样本大小计算:从业者指南","authors":"Brendon McConnell, Marcos Vera-Hernández","doi":"10.1111/1475-5890.70005","DOIUrl":null,"url":null,"abstract":"<p>Basic methods to compute required sample sizes are well understood and supported by widely available software. However, researchers often oversimplify their sample size calculations, overlooking relevant features of their experimental design. This paper compiles and systematises existing methods for sample size calculations for continuous and binary outcomes, both with and without covariates, and for both clustered and non-clustered randomised controlled trials. We present formulae accommodating panel data structures and uneven designs, and provide guidance on optimally allocating sample size between the number of clusters and the number of units per cluster. In addition, we discuss how to adjust calculations for multiple hypothesis testing and how to estimate power in more complex designs using simulation methods.</p>","PeriodicalId":51602,"journal":{"name":"Fiscal Studies","volume":"46 3","pages":"323-348"},"PeriodicalIF":1.3000,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1475-5890.70005","citationCount":"0","resultStr":"{\"title\":\"Going beyond simple sample size calculations: a practitioner's guide\",\"authors\":\"Brendon McConnell, Marcos Vera-Hernández\",\"doi\":\"10.1111/1475-5890.70005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Basic methods to compute required sample sizes are well understood and supported by widely available software. However, researchers often oversimplify their sample size calculations, overlooking relevant features of their experimental design. This paper compiles and systematises existing methods for sample size calculations for continuous and binary outcomes, both with and without covariates, and for both clustered and non-clustered randomised controlled trials. We present formulae accommodating panel data structures and uneven designs, and provide guidance on optimally allocating sample size between the number of clusters and the number of units per cluster. In addition, we discuss how to adjust calculations for multiple hypothesis testing and how to estimate power in more complex designs using simulation methods.</p>\",\"PeriodicalId\":51602,\"journal\":{\"name\":\"Fiscal Studies\",\"volume\":\"46 3\",\"pages\":\"323-348\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1475-5890.70005\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fiscal Studies\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1475-5890.70005\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fiscal Studies","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1475-5890.70005","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Going beyond simple sample size calculations: a practitioner's guide
Basic methods to compute required sample sizes are well understood and supported by widely available software. However, researchers often oversimplify their sample size calculations, overlooking relevant features of their experimental design. This paper compiles and systematises existing methods for sample size calculations for continuous and binary outcomes, both with and without covariates, and for both clustered and non-clustered randomised controlled trials. We present formulae accommodating panel data structures and uneven designs, and provide guidance on optimally allocating sample size between the number of clusters and the number of units per cluster. In addition, we discuss how to adjust calculations for multiple hypothesis testing and how to estimate power in more complex designs using simulation methods.
期刊介绍:
The Institute for Fiscal Studies publishes the journal Fiscal Studies, which serves as a bridge between academic research and policy. This esteemed journal, established in 1979, has gained global recognition for its publication of high-quality and original research papers. The articles, authored by prominent academics, policymakers, and practitioners, are presented in an accessible format, ensuring a broad international readership.