{"title":"协方差分析(ANCOVA)","authors":"D. Clark-Carter","doi":"10.4324/9780203870709-30","DOIUrl":null,"url":null,"abstract":"Introduction A common task in research is to compare the averages of two or more populations (groups). We might want to compare the income level of two regions, the nitrogen content of three lakes, or the effectiveness of four drugs. The one-way analysis of variance compares the means of two or more groups to determine if at least one mean is different from the others. The F test is used to determine statistical significance. Analysis of Covariance (ANCOVA) is an extension of the one-way analysis of variance model that adds quantitative variables (covariates). When used, it is assumed that their inclusion will reduce the size of the error variance and thus increase the power of the design.","PeriodicalId":399147,"journal":{"name":"Quantitative Psychological Research","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of covariance (ANCOVA)\",\"authors\":\"D. Clark-Carter\",\"doi\":\"10.4324/9780203870709-30\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Introduction A common task in research is to compare the averages of two or more populations (groups). We might want to compare the income level of two regions, the nitrogen content of three lakes, or the effectiveness of four drugs. The one-way analysis of variance compares the means of two or more groups to determine if at least one mean is different from the others. The F test is used to determine statistical significance. Analysis of Covariance (ANCOVA) is an extension of the one-way analysis of variance model that adds quantitative variables (covariates). When used, it is assumed that their inclusion will reduce the size of the error variance and thus increase the power of the design.\",\"PeriodicalId\":399147,\"journal\":{\"name\":\"Quantitative Psychological Research\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quantitative Psychological Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4324/9780203870709-30\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Psychological Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4324/9780203870709-30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Introduction A common task in research is to compare the averages of two or more populations (groups). We might want to compare the income level of two regions, the nitrogen content of three lakes, or the effectiveness of four drugs. The one-way analysis of variance compares the means of two or more groups to determine if at least one mean is different from the others. The F test is used to determine statistical significance. Analysis of Covariance (ANCOVA) is an extension of the one-way analysis of variance model that adds quantitative variables (covariates). When used, it is assumed that their inclusion will reduce the size of the error variance and thus increase the power of the design.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
