{"title":"CHI PLAY的统计显著性检验:提高透明度的挑战和机遇","authors":"Jan B. Vornhagen, April Tyack, Elisa D. Mekler","doi":"10.1145/3410404.3414229","DOIUrl":null,"url":null,"abstract":"Statistical Significance Testing -- or Null Hypothesis Significance Testing (NHST) -- is common to quantitative CHI PLAY research. Drawing from recent work in HCI and psychology promoting transparent statistics and the reduction of questionable research practices, we systematically review the reporting quality of 119 CHI PLAY papers using NHST (data and analysis plan at OSF.io). We find that over half of these papers employ NHST without specific statistical hypotheses or research questions, which may risk the proliferation of false positive findings. Moreover, we observe inconsistencies in the reporting of sample sizes and statistical tests. These issues reflect fundamental incompatibilities between NHST and the frequently exploratory work common to CHI PLAY. We discuss the complementary roles of exploratory and confirmatory research, and provide a template for more transparent research and reporting practices.","PeriodicalId":92838,"journal":{"name":"Proceedings of the ... Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play","volume":"42 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"Statistical Significance Testing at CHI PLAY: Challenges and Opportunities for More Transparency\",\"authors\":\"Jan B. Vornhagen, April Tyack, Elisa D. Mekler\",\"doi\":\"10.1145/3410404.3414229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Statistical Significance Testing -- or Null Hypothesis Significance Testing (NHST) -- is common to quantitative CHI PLAY research. Drawing from recent work in HCI and psychology promoting transparent statistics and the reduction of questionable research practices, we systematically review the reporting quality of 119 CHI PLAY papers using NHST (data and analysis plan at OSF.io). We find that over half of these papers employ NHST without specific statistical hypotheses or research questions, which may risk the proliferation of false positive findings. Moreover, we observe inconsistencies in the reporting of sample sizes and statistical tests. These issues reflect fundamental incompatibilities between NHST and the frequently exploratory work common to CHI PLAY. We discuss the complementary roles of exploratory and confirmatory research, and provide a template for more transparent research and reporting practices.\",\"PeriodicalId\":92838,\"journal\":{\"name\":\"Proceedings of the ... Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play\",\"volume\":\"42 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ... Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3410404.3414229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3410404.3414229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical Significance Testing at CHI PLAY: Challenges and Opportunities for More Transparency
Statistical Significance Testing -- or Null Hypothesis Significance Testing (NHST) -- is common to quantitative CHI PLAY research. Drawing from recent work in HCI and psychology promoting transparent statistics and the reduction of questionable research practices, we systematically review the reporting quality of 119 CHI PLAY papers using NHST (data and analysis plan at OSF.io). We find that over half of these papers employ NHST without specific statistical hypotheses or research questions, which may risk the proliferation of false positive findings. Moreover, we observe inconsistencies in the reporting of sample sizes and statistical tests. These issues reflect fundamental incompatibilities between NHST and the frequently exploratory work common to CHI PLAY. We discuss the complementary roles of exploratory and confirmatory research, and provide a template for more transparent research and reporting practices.