{"title":"FAVis:心理研究因素分析的可视化分析","authors":"Yikai Lu, Chaoli Wang","doi":"arxiv-2407.14072","DOIUrl":null,"url":null,"abstract":"Psychological research often involves understanding psychological constructs\nthrough conducting factor analysis on data collected by a questionnaire, which\ncan comprise hundreds of questions. Without interactive systems for\ninterpreting factor models, researchers are frequently exposed to subjectivity,\npotentially leading to misinterpretations or overlooked crucial information.\nThis paper introduces FAVis, a novel interactive visualization tool designed to\naid researchers in interpreting and evaluating factor analysis results. FAVis\nenhances the understanding of relationships between variables and factors by\nsupporting multiple views for visualizing factor loadings and correlations,\nallowing users to analyze information from various perspectives. The primary\nfeature of FAVis is to enable users to set optimal thresholds for factor\nloadings to balance clarity and information retention. FAVis also allows users\nto assign tags to variables, enhancing the understanding of factors by linking\nthem to their associated psychological constructs. Our user study demonstrates\nthe utility of FAVis in various tasks.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FAVis: Visual Analytics of Factor Analysis for Psychological Research\",\"authors\":\"Yikai Lu, Chaoli Wang\",\"doi\":\"arxiv-2407.14072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Psychological research often involves understanding psychological constructs\\nthrough conducting factor analysis on data collected by a questionnaire, which\\ncan comprise hundreds of questions. Without interactive systems for\\ninterpreting factor models, researchers are frequently exposed to subjectivity,\\npotentially leading to misinterpretations or overlooked crucial information.\\nThis paper introduces FAVis, a novel interactive visualization tool designed to\\naid researchers in interpreting and evaluating factor analysis results. FAVis\\nenhances the understanding of relationships between variables and factors by\\nsupporting multiple views for visualizing factor loadings and correlations,\\nallowing users to analyze information from various perspectives. The primary\\nfeature of FAVis is to enable users to set optimal thresholds for factor\\nloadings to balance clarity and information retention. FAVis also allows users\\nto assign tags to variables, enhancing the understanding of factors by linking\\nthem to their associated psychological constructs. Our user study demonstrates\\nthe utility of FAVis in various tasks.\",\"PeriodicalId\":501323,\"journal\":{\"name\":\"arXiv - STAT - Other Statistics\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - STAT - Other Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.14072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Other Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.14072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FAVis: Visual Analytics of Factor Analysis for Psychological Research
Psychological research often involves understanding psychological constructs
through conducting factor analysis on data collected by a questionnaire, which
can comprise hundreds of questions. Without interactive systems for
interpreting factor models, researchers are frequently exposed to subjectivity,
potentially leading to misinterpretations or overlooked crucial information.
This paper introduces FAVis, a novel interactive visualization tool designed to
aid researchers in interpreting and evaluating factor analysis results. FAVis
enhances the understanding of relationships between variables and factors by
supporting multiple views for visualizing factor loadings and correlations,
allowing users to analyze information from various perspectives. The primary
feature of FAVis is to enable users to set optimal thresholds for factor
loadings to balance clarity and information retention. FAVis also allows users
to assign tags to variables, enhancing the understanding of factors by linking
them to their associated psychological constructs. Our user study demonstrates
the utility of FAVis in various tasks.