{"title":"二元响应的回归不连续及外推处理的局部极大似然估计。","authors":"Goeun Lee, Myoung-Jae Lee","doi":"10.1177/0193841X221105968","DOIUrl":null,"url":null,"abstract":"<p><p>Regression discontinuity is popular in finding treatment/policy effects when the treatment is determined by a continuous variable crossing a cutoff. Typically, a local linear regression (LLR) estimator is used to find the effects. For binary response, however, LLR is not suitable in extrapolating the treatment, as in doubling/tripling the treatment dose/intensity. The reason is that doubling/tripling the LLR estimate can give a number out of the bound <math><mrow><mrow><mo>[</mo><mrow><mo>-</mo><mn>1</mn><mo>,</mo><mtext> </mtext><mn>1</mn></mrow><mo>]</mo></mrow></mrow></math>, despite that the effect should be a change in probability. We propose local maximum likelihood estimators which overcome these shortcomings, while giving almost the same estimates as the LLR estimator does for the original treatment. A simulation study and an empirical analysis for effects of an income subsidy program on religion demonstrate these points.</p>","PeriodicalId":47533,"journal":{"name":"Evaluation Review","volume":"47 2","pages":"182-208"},"PeriodicalIF":3.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Regression Discontinuity for Binary Response and Local Maximum Likelihood Estimator to Extrapolate Treatment.\",\"authors\":\"Goeun Lee, Myoung-Jae Lee\",\"doi\":\"10.1177/0193841X221105968\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Regression discontinuity is popular in finding treatment/policy effects when the treatment is determined by a continuous variable crossing a cutoff. Typically, a local linear regression (LLR) estimator is used to find the effects. For binary response, however, LLR is not suitable in extrapolating the treatment, as in doubling/tripling the treatment dose/intensity. The reason is that doubling/tripling the LLR estimate can give a number out of the bound <math><mrow><mrow><mo>[</mo><mrow><mo>-</mo><mn>1</mn><mo>,</mo><mtext> </mtext><mn>1</mn></mrow><mo>]</mo></mrow></mrow></math>, despite that the effect should be a change in probability. We propose local maximum likelihood estimators which overcome these shortcomings, while giving almost the same estimates as the LLR estimator does for the original treatment. A simulation study and an empirical analysis for effects of an income subsidy program on religion demonstrate these points.</p>\",\"PeriodicalId\":47533,\"journal\":{\"name\":\"Evaluation Review\",\"volume\":\"47 2\",\"pages\":\"182-208\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Evaluation Review\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/0193841X221105968\",\"RegionNum\":4,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Evaluation Review","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/0193841X221105968","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Regression Discontinuity for Binary Response and Local Maximum Likelihood Estimator to Extrapolate Treatment.
Regression discontinuity is popular in finding treatment/policy effects when the treatment is determined by a continuous variable crossing a cutoff. Typically, a local linear regression (LLR) estimator is used to find the effects. For binary response, however, LLR is not suitable in extrapolating the treatment, as in doubling/tripling the treatment dose/intensity. The reason is that doubling/tripling the LLR estimate can give a number out of the bound , despite that the effect should be a change in probability. We propose local maximum likelihood estimators which overcome these shortcomings, while giving almost the same estimates as the LLR estimator does for the original treatment. A simulation study and an empirical analysis for effects of an income subsidy program on religion demonstrate these points.
期刊介绍:
Evaluation Review is the forum for researchers, planners, and policy makers engaged in the development, implementation, and utilization of studies aimed at the betterment of the human condition. The Editors invite submission of papers reporting the findings of evaluation studies in such fields as child development, health, education, income security, manpower, mental health, criminal justice, and the physical and social environments. In addition, Evaluation Review will contain articles on methodological developments, discussions of the state of the art, and commentaries on issues related to the application of research results. Special features will include periodic review essays, "research briefs", and "craft reports".