{"title":"马萨诸塞州医疗改革降低了死亡率吗?根据随机化推理","authors":"R. Kaestner","doi":"10.1080/2330443X.2015.1102667","DOIUrl":null,"url":null,"abstract":"ABSTRACT In an earlier article, Sommers, Long, and Baicker concluded that health care reform in Massachusetts was associated with a significant decrease in mortality. I replicate the findings from this study and present p-values for the parameter estimates reported by Sommers, Long, and Baicker that are based on an alternative and valid approach to inference referred to as randomization inference. I find that estimates of the treatment effects produced by Sommers, Long, and Baicker are not statistically significant when p-values are based on randomization inference methods. Indeed, the p-values of the estimates reported in Sommers, Long, and Baicker derived by the randomization inference method range from 0.22 to 0.78. Therefore, the authors’ conclusion that health reform in Massachusetts was associated with a decline in mortality is not justified. The Sommers, Long, and Baicker analysis is largely uninformative with respect to the true effect of reform on mortality because it does not have adequate statistical power to detect plausible effect sizes.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2015.1102667","citationCount":"39","resultStr":"{\"title\":\"Did Massachusetts Health Care Reform Lower Mortality? No According to Randomization Inference\",\"authors\":\"R. Kaestner\",\"doi\":\"10.1080/2330443X.2015.1102667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT In an earlier article, Sommers, Long, and Baicker concluded that health care reform in Massachusetts was associated with a significant decrease in mortality. I replicate the findings from this study and present p-values for the parameter estimates reported by Sommers, Long, and Baicker that are based on an alternative and valid approach to inference referred to as randomization inference. I find that estimates of the treatment effects produced by Sommers, Long, and Baicker are not statistically significant when p-values are based on randomization inference methods. Indeed, the p-values of the estimates reported in Sommers, Long, and Baicker derived by the randomization inference method range from 0.22 to 0.78. Therefore, the authors’ conclusion that health reform in Massachusetts was associated with a decline in mortality is not justified. The Sommers, Long, and Baicker analysis is largely uninformative with respect to the true effect of reform on mortality because it does not have adequate statistical power to detect plausible effect sizes.\",\"PeriodicalId\":43397,\"journal\":{\"name\":\"Statistics and Public Policy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2016-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/2330443X.2015.1102667\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics and Public Policy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/2330443X.2015.1102667\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, MATHEMATICAL METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics and Public Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2330443X.2015.1102667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
Did Massachusetts Health Care Reform Lower Mortality? No According to Randomization Inference
ABSTRACT In an earlier article, Sommers, Long, and Baicker concluded that health care reform in Massachusetts was associated with a significant decrease in mortality. I replicate the findings from this study and present p-values for the parameter estimates reported by Sommers, Long, and Baicker that are based on an alternative and valid approach to inference referred to as randomization inference. I find that estimates of the treatment effects produced by Sommers, Long, and Baicker are not statistically significant when p-values are based on randomization inference methods. Indeed, the p-values of the estimates reported in Sommers, Long, and Baicker derived by the randomization inference method range from 0.22 to 0.78. Therefore, the authors’ conclusion that health reform in Massachusetts was associated with a decline in mortality is not justified. The Sommers, Long, and Baicker analysis is largely uninformative with respect to the true effect of reform on mortality because it does not have adequate statistical power to detect plausible effect sizes.