Pub Date : 2021-04-01DOI: 10.1017/9781108777919.002
J. Druckman, D. Green
Experimental political science has transformed in the last decade. The use of experiments has dramatically increased throughout the discipline, and technological and sociological changes have altered how political scientists use experiments. We chart the transformation of experiments and discuss new challenges that experimentalists face. We then outline how the contributions to this volume will help scholars and practitioners conduct high-quality experiments.
{"title":"A New Era of Experimental Political Science","authors":"J. Druckman, D. Green","doi":"10.1017/9781108777919.002","DOIUrl":"https://doi.org/10.1017/9781108777919.002","url":null,"abstract":"Experimental political science has transformed in the last decade. The use of experiments has dramatically increased throughout the discipline, and technological and sociological changes have altered how political scientists use experiments. We chart the transformation of experiments and discuss new challenges that experimentalists face. We then outline how the contributions to this volume will help scholars and practitioners conduct high-quality experiments.","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117068625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-01DOI: 10.1017/9781108777919.033
Amanda Clayton, Georgia Anderson-Nilsson
{"title":"Gender Experiments in Comparative Politics","authors":"Amanda Clayton, Georgia Anderson-Nilsson","doi":"10.1017/9781108777919.033","DOIUrl":"https://doi.org/10.1017/9781108777919.033","url":null,"abstract":"","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127508486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-03-31DOI: 10.1017/9781108777919.020
Marc Ratkovic
Experiments often focus on recovering an average effect of a treatment on an outcome. A subgroup analysis involves identifying subgroups of observations for which the treatment is particularly efficacious or deleterious. Since these subgroups are not preregistered but instead discovered from the data, significant inferential issues emerge. We discuss methods for conduct honest inference on subgroups, meaning generating valid p -values and confidence intervals which ac-count for the fact that the subgroups were not specified a priori . Central to this approach is the split-sample strategy, where half the data is used to identify ef-fects and the other half to test them. After an intuitive and formal discussion of these issues, we provide simulation evidence and two examples illustrating these concepts in practice.
{"title":"Subgroup Analysis: Pitfalls, Promise, and Honesty","authors":"Marc Ratkovic","doi":"10.1017/9781108777919.020","DOIUrl":"https://doi.org/10.1017/9781108777919.020","url":null,"abstract":"Experiments often focus on recovering an average effect of a treatment on an outcome. A subgroup analysis involves identifying subgroups of observations for which the treatment is particularly efficacious or deleterious. Since these subgroups are not preregistered but instead discovered from the data, significant inferential issues emerge. We discuss methods for conduct honest inference on subgroups, meaning generating valid p -values and confidence intervals which ac-count for the fact that the subgroups were not specified a priori . Central to this approach is the split-sample strategy, where half the data is used to identify ef-fects and the other half to test them. After an intuitive and formal discussion of these issues, we provide simulation evidence and two examples illustrating these concepts in practice.","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125800483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-01DOI: 10.1017/9781108777919.008
R. Titiunik
The term natural experiment is used inconsistently. In one interpretation, it refers to an experiment where a treatment is randomly assigned by someone other than the researcher. In another interpretation, it refers to a study in which there is no controlled random assignment, but treatment is assigned by some external factor in a way that loosely resembles a randomized experiment---often described as an "as if random" assignment. In yet another interpretation, it refers to any non-randomized study that compares a treatment to a control group, without any specific requirements on how the treatment is assigned. I introduce an alternative definition that seeks to clarify the integral features of natural experiments and at the same time distinguish them from randomized controlled experiments. I define a natural experiment as a research study where the treatment assignment mechanism (i) is neither designed nor implemented by the researcher, (ii) is unknown to the researcher, and (iii) is probabilistic by virtue of depending on an external factor. The main message of this definition is that the difference between a randomized controlled experiment and a natural experiment is not a matter of degree, but of essence, and thus conceptualizing a natural experiment as a research design akin to a randomized experiment is neither rigorous nor a useful guide to empirical analysis. Using my alternative definition, I discuss how a natural experiment differs from a traditional observational study, and offer practical recommendations for researchers who wish to use natural experiments to study causal effects.
{"title":"Natural Experiments","authors":"R. Titiunik","doi":"10.1017/9781108777919.008","DOIUrl":"https://doi.org/10.1017/9781108777919.008","url":null,"abstract":"The term natural experiment is used inconsistently. In one interpretation, it refers to an experiment where a treatment is randomly assigned by someone other than the researcher. In another interpretation, it refers to a study in which there is no controlled random assignment, but treatment is assigned by some external factor in a way that loosely resembles a randomized experiment---often described as an \"as if random\" assignment. In yet another interpretation, it refers to any non-randomized study that compares a treatment to a control group, without any specific requirements on how the treatment is assigned. I introduce an alternative definition that seeks to clarify the integral features of natural experiments and at the same time distinguish them from randomized controlled experiments. I define a natural experiment as a research study where the treatment assignment mechanism (i) is neither designed nor implemented by the researcher, (ii) is unknown to the researcher, and (iii) is probabilistic by virtue of depending on an external factor. The main message of this definition is that the difference between a randomized controlled experiment and a natural experiment is not a matter of degree, but of essence, and thus conceptualizing a natural experiment as a research design akin to a randomized experiment is neither rigorous nor a useful guide to empirical analysis. Using my alternative definition, I discuss how a natural experiment differs from a traditional observational study, and offer practical recommendations for researchers who wish to use natural experiments to study causal effects.","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117221280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1017/9781108777919.029
{"title":"Using Experiments to study Identity","authors":"","doi":"10.1017/9781108777919.029","DOIUrl":"https://doi.org/10.1017/9781108777919.029","url":null,"abstract":"","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121984683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1017/9781108777919.018
{"title":"Experimental Analys is and Presentation","authors":"","doi":"10.1017/9781108777919.018","DOIUrl":"https://doi.org/10.1017/9781108777919.018","url":null,"abstract":"","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126390128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1017/9781108777919.023
{"title":"Experimental Reliability and Generalizability","authors":"","doi":"10.1017/9781108777919.023","DOIUrl":"https://doi.org/10.1017/9781108777919.023","url":null,"abstract":"","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124424465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1017/9781108777919.015
{"title":"Experimental Treatments and Measures","authors":"","doi":"10.1017/9781108777919.015","DOIUrl":"https://doi.org/10.1017/9781108777919.015","url":null,"abstract":"","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115964696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1017/9781108777919.034
{"title":"Using Experiments to Study Government Actions","authors":"","doi":"10.1017/9781108777919.034","DOIUrl":"https://doi.org/10.1017/9781108777919.034","url":null,"abstract":"","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116821205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1017/9781108777919.010
A. Reinhorn
{"title":"Experimental Data","authors":"A. Reinhorn","doi":"10.1017/9781108777919.010","DOIUrl":"https://doi.org/10.1017/9781108777919.010","url":null,"abstract":"","PeriodicalId":254604,"journal":{"name":"Advances in Experimental Political Science","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116273026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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