{"title":"放弃操纵检查失败的受试者会对你的结果产生偏见:一个例证案例","authors":"Simon Varaine","doi":"10.1017/XPS.2022.28","DOIUrl":null,"url":null,"abstract":"Abstract Manipulations checks are postexperimental measures widely used to verify that subjects understood the treatment. Some researchers drop subjects who failed manipulation checks in order to limit the analyses to attentive subjects. This short report offers a novel illustration on how this practice may bias experimental results: in the present case, through confirming a hypothesis that is likely false. In a survey experiment, subjects were primed with a fictional news story depicting an economic decline versus prosperity. Subjects were then asked whether the news story depicted an economic decline or prosperity. Results indicate that responses to this manipulation check captured subjects’ preexisting beliefs about the economic situation. As a consequence, dropping subjects who failed the manipulation check mixes the effects of preexisting and induced beliefs, increasing the risk of false positive findings. Researchers should avoid dropping subjects based on posttreatment measures and rely on pretreatment measures of attentiveness.","PeriodicalId":37558,"journal":{"name":"Journal of Experimental Political Science","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"How Dropping Subjects Who Failed Manipulation Checks Can Bias Your Results: An Illustrative Case\",\"authors\":\"Simon Varaine\",\"doi\":\"10.1017/XPS.2022.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Manipulations checks are postexperimental measures widely used to verify that subjects understood the treatment. Some researchers drop subjects who failed manipulation checks in order to limit the analyses to attentive subjects. This short report offers a novel illustration on how this practice may bias experimental results: in the present case, through confirming a hypothesis that is likely false. In a survey experiment, subjects were primed with a fictional news story depicting an economic decline versus prosperity. Subjects were then asked whether the news story depicted an economic decline or prosperity. Results indicate that responses to this manipulation check captured subjects’ preexisting beliefs about the economic situation. As a consequence, dropping subjects who failed the manipulation check mixes the effects of preexisting and induced beliefs, increasing the risk of false positive findings. Researchers should avoid dropping subjects based on posttreatment measures and rely on pretreatment measures of attentiveness.\",\"PeriodicalId\":37558,\"journal\":{\"name\":\"Journal of Experimental Political Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2022-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Experimental Political Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1017/XPS.2022.28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"POLITICAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Experimental Political Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/XPS.2022.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"POLITICAL SCIENCE","Score":null,"Total":0}
How Dropping Subjects Who Failed Manipulation Checks Can Bias Your Results: An Illustrative Case
Abstract Manipulations checks are postexperimental measures widely used to verify that subjects understood the treatment. Some researchers drop subjects who failed manipulation checks in order to limit the analyses to attentive subjects. This short report offers a novel illustration on how this practice may bias experimental results: in the present case, through confirming a hypothesis that is likely false. In a survey experiment, subjects were primed with a fictional news story depicting an economic decline versus prosperity. Subjects were then asked whether the news story depicted an economic decline or prosperity. Results indicate that responses to this manipulation check captured subjects’ preexisting beliefs about the economic situation. As a consequence, dropping subjects who failed the manipulation check mixes the effects of preexisting and induced beliefs, increasing the risk of false positive findings. Researchers should avoid dropping subjects based on posttreatment measures and rely on pretreatment measures of attentiveness.
期刊介绍:
The Journal of Experimental Political Science (JEPS) features cutting-edge research that utilizes experimental methods or experimental reasoning based on naturally occurring data. We define experimental methods broadly: research featuring random (or quasi-random) assignment of subjects to different treatments in an effort to isolate causal relationships in the sphere of politics. JEPS embraces all of the different types of experiments carried out as part of political science research, including survey experiments, laboratory experiments, field experiments, lab experiments in the field, natural and neurological experiments. We invite authors to submit concise articles (around 4000 words or fewer) that immediately address the subject of the research. We do not require lengthy explanations regarding and justifications of the experimental method. Nor do we expect extensive literature reviews of pros and cons of the methodological approaches involved in the experiment unless the goal of the article is to explore these methodological issues. We expect readers to be familiar with experimental methods and therefore to not need pages of literature reviews to be convinced that experimental methods are a legitimate methodological approach. We will consider longer articles in rare, but appropriate cases, as in the following examples: when a new experimental method or approach is being introduced and discussed or when novel theoretical results are being evaluated through experimentation. Finally, we strongly encourage authors to submit manuscripts that showcase informative null findings or inconsistent results from well-designed, executed, and analyzed experiments.