{"title":"数据检测工具:心理学中检测数据和结果异常的统计方法综述。","authors":"Gabriel Crone, Christopher D Green","doi":"10.1177/09593543241311861","DOIUrl":null,"url":null,"abstract":"<p><p>In psychology, it is largely assumed that researchers collect real data and analyze them honestly-that is, it is assumed that data fabrication seldom occurs. While data fabrication is a rare phenomenon, estimates suggest that it occurs frequently enough to be a concern. To this end, statistical tools have been created to detect and deter data fabrication. Often, these tools either assess raw data, or assess summary statistical information. However, very few studies have attempted to review these tools, and of those that have, certain tools were excluded. The purpose of the present study was to review a collection of existing statistical tools to detect data fabrication, assess their strengths and limitations, and consider their place in psychological practice. The major strengths of the tools included their comprehensiveness and rigor, while their limitations were in their stringent criteria to run and in that they were impractical to implement.</p>","PeriodicalId":47640,"journal":{"name":"Theory & Psychology","volume":"35 3","pages":"359-380"},"PeriodicalIF":1.1000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121900/pdf/","citationCount":"0","resultStr":"{\"title\":\"Tools of the data detective: A review of statistical methods to detect data and result anomalies in psychology.\",\"authors\":\"Gabriel Crone, Christopher D Green\",\"doi\":\"10.1177/09593543241311861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In psychology, it is largely assumed that researchers collect real data and analyze them honestly-that is, it is assumed that data fabrication seldom occurs. While data fabrication is a rare phenomenon, estimates suggest that it occurs frequently enough to be a concern. To this end, statistical tools have been created to detect and deter data fabrication. Often, these tools either assess raw data, or assess summary statistical information. However, very few studies have attempted to review these tools, and of those that have, certain tools were excluded. The purpose of the present study was to review a collection of existing statistical tools to detect data fabrication, assess their strengths and limitations, and consider their place in psychological practice. The major strengths of the tools included their comprehensiveness and rigor, while their limitations were in their stringent criteria to run and in that they were impractical to implement.</p>\",\"PeriodicalId\":47640,\"journal\":{\"name\":\"Theory & Psychology\",\"volume\":\"35 3\",\"pages\":\"359-380\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12121900/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theory & Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1177/09593543241311861\",\"RegionNum\":4,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory & Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/09593543241311861","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/1 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
Tools of the data detective: A review of statistical methods to detect data and result anomalies in psychology.
In psychology, it is largely assumed that researchers collect real data and analyze them honestly-that is, it is assumed that data fabrication seldom occurs. While data fabrication is a rare phenomenon, estimates suggest that it occurs frequently enough to be a concern. To this end, statistical tools have been created to detect and deter data fabrication. Often, these tools either assess raw data, or assess summary statistical information. However, very few studies have attempted to review these tools, and of those that have, certain tools were excluded. The purpose of the present study was to review a collection of existing statistical tools to detect data fabrication, assess their strengths and limitations, and consider their place in psychological practice. The major strengths of the tools included their comprehensiveness and rigor, while their limitations were in their stringent criteria to run and in that they were impractical to implement.
期刊介绍:
Theory & Psychology is a fully peer reviewed forum for theoretical and meta-theoretical analysis in psychology. It focuses on the emergent themes at the centre of contemporary psychological debate. Its principal aim is to foster theoretical dialogue and innovation within the discipline, serving an integrative role for a wide psychological audience. Theory & Psychology publishes scholarly and expository papers which explore significant theoretical developments within and across such specific sub-areas as: cognitive, social, personality, developmental, clinical, perceptual or biological psychology.