{"title":"教育环境中抽样的简要指南","authors":"A. George","doi":"10.20982/tqmp.17.3.p286","DOIUrl":null,"url":null,"abstract":"This tutorial gives an overview of sampling techniques commonly used in the field of education such as simple randomized sampling, stratification methods and (multistage) cluster randomized sampling. Advantages and disadvantages of these techniques are describedwithout diving too deep into sampling theory. Instead, each technique is exemplified with data and program code in R. Finally, all presented techniques are combined to show the complexity of samples in famous educational large-scale studies such as PISA. Again an example with R code illustrates the theoretical descriptions.","PeriodicalId":93055,"journal":{"name":"The quantitative methods for psychology","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A brief guide to sampling in educational settings\",\"authors\":\"A. George\",\"doi\":\"10.20982/tqmp.17.3.p286\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This tutorial gives an overview of sampling techniques commonly used in the field of education such as simple randomized sampling, stratification methods and (multistage) cluster randomized sampling. Advantages and disadvantages of these techniques are describedwithout diving too deep into sampling theory. Instead, each technique is exemplified with data and program code in R. Finally, all presented techniques are combined to show the complexity of samples in famous educational large-scale studies such as PISA. Again an example with R code illustrates the theoretical descriptions.\",\"PeriodicalId\":93055,\"journal\":{\"name\":\"The quantitative methods for psychology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The quantitative methods for psychology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20982/tqmp.17.3.p286\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The quantitative methods for psychology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20982/tqmp.17.3.p286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This tutorial gives an overview of sampling techniques commonly used in the field of education such as simple randomized sampling, stratification methods and (multistage) cluster randomized sampling. Advantages and disadvantages of these techniques are describedwithout diving too deep into sampling theory. Instead, each technique is exemplified with data and program code in R. Finally, all presented techniques are combined to show the complexity of samples in famous educational large-scale studies such as PISA. Again an example with R code illustrates the theoretical descriptions.