{"title":"每个集群有多少个案例?具有线性结果的两级聚类随机评估中相对于最小可检测效应的每簇单位数的可操作性","authors":"E. Hedberg","doi":"10.1177/10982140221134618","DOIUrl":null,"url":null,"abstract":"In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical power. Typically, researchers state that “about 30 units per cluster” is the most that will yield benefit towards statistical precision. To avoid rules of thumb not grounded in statistical theory and practical considerations, and instead provide guidance for this question, the ratio of the minimum detectable effect size (MDES) to the larger MDES with one less unit per cluster is related to the key parameters of the cluster randomized design. Formulas for this subsequent difference effect size ratio (SDESR) at a given number of units are provided, as are formulas for finding the number of units for an assumed SDESR. In general, the point of diminishing returns occurs with smaller numbers of units for larger values of the intraclass correlation.","PeriodicalId":51449,"journal":{"name":"American Journal of Evaluation","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How Many Cases per Cluster? Operationalizing the Number of Units per Cluster Relative to Minimum Detectable Effects in Two-Level Cluster Randomized Evaluations with Linear Outcomes\",\"authors\":\"E. Hedberg\",\"doi\":\"10.1177/10982140221134618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical power. Typically, researchers state that “about 30 units per cluster” is the most that will yield benefit towards statistical precision. To avoid rules of thumb not grounded in statistical theory and practical considerations, and instead provide guidance for this question, the ratio of the minimum detectable effect size (MDES) to the larger MDES with one less unit per cluster is related to the key parameters of the cluster randomized design. Formulas for this subsequent difference effect size ratio (SDESR) at a given number of units are provided, as are formulas for finding the number of units for an assumed SDESR. In general, the point of diminishing returns occurs with smaller numbers of units for larger values of the intraclass correlation.\",\"PeriodicalId\":51449,\"journal\":{\"name\":\"American Journal of Evaluation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Evaluation\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/10982140221134618\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Evaluation","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/10982140221134618","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
How Many Cases per Cluster? Operationalizing the Number of Units per Cluster Relative to Minimum Detectable Effects in Two-Level Cluster Randomized Evaluations with Linear Outcomes
In cluster randomized evaluations, a treatment or intervention is randomly assigned to a set of clusters each with constituent individual units of observations (e.g., student units that attend schools, which are assigned to treatment). One consideration of these designs is how many units are needed per cluster to achieve adequate statistical power. Typically, researchers state that “about 30 units per cluster” is the most that will yield benefit towards statistical precision. To avoid rules of thumb not grounded in statistical theory and practical considerations, and instead provide guidance for this question, the ratio of the minimum detectable effect size (MDES) to the larger MDES with one less unit per cluster is related to the key parameters of the cluster randomized design. Formulas for this subsequent difference effect size ratio (SDESR) at a given number of units are provided, as are formulas for finding the number of units for an assumed SDESR. In general, the point of diminishing returns occurs with smaller numbers of units for larger values of the intraclass correlation.
期刊介绍:
The American Journal of Evaluation (AJE) publishes original papers about the methods, theory, practice, and findings of evaluation. The general goal of AJE is to present the best work in and about evaluation, in order to improve the knowledge base and practice of its readers. Because the field of evaluation is diverse, with different intellectual traditions, approaches to practice, and domains of application, the papers published in AJE will reflect this diversity. Nevertheless, preference is given to papers that are likely to be of interest to a wide range of evaluators and that are written to be accessible to most readers.