{"title":"使用预测方法评估观察结果和衡量重要性","authors":"William M. Briggs","doi":"10.1108/ajeb-05-2024-0066","DOIUrl":null,"url":null,"abstract":"PurposeThis study aims to find suitable replacements for hypothesis testing and variable-importance measures.Design/methodology/approachThis study explores under-used predictive methods.FindingsThe study's hypothesis testing can and should be replaced by predictive methods. It is the only way to know if models have any value.Originality/valueThis is the first time predictive methods have been used to demonstrate measure and variable importance. Hypothesis testing can never prove the goodness of models. Only predictive methods can.","PeriodicalId":504795,"journal":{"name":"Asian Journal of Economics and Banking","volume":"16 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using predictive methods to assess observation and measure importance\",\"authors\":\"William M. Briggs\",\"doi\":\"10.1108/ajeb-05-2024-0066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PurposeThis study aims to find suitable replacements for hypothesis testing and variable-importance measures.Design/methodology/approachThis study explores under-used predictive methods.FindingsThe study's hypothesis testing can and should be replaced by predictive methods. It is the only way to know if models have any value.Originality/valueThis is the first time predictive methods have been used to demonstrate measure and variable importance. Hypothesis testing can never prove the goodness of models. Only predictive methods can.\",\"PeriodicalId\":504795,\"journal\":{\"name\":\"Asian Journal of Economics and Banking\",\"volume\":\"16 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Economics and Banking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/ajeb-05-2024-0066\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Economics and Banking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ajeb-05-2024-0066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using predictive methods to assess observation and measure importance
PurposeThis study aims to find suitable replacements for hypothesis testing and variable-importance measures.Design/methodology/approachThis study explores under-used predictive methods.FindingsThe study's hypothesis testing can and should be replaced by predictive methods. It is the only way to know if models have any value.Originality/valueThis is the first time predictive methods have been used to demonstrate measure and variable importance. Hypothesis testing can never prove the goodness of models. Only predictive methods can.