[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-160156-en":3,"doc-seo-160156-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},160156,2336474459895,"Gloria","https://ap-avatar.wpscdn.com/avatar/22000baeef7a5ed0655?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786071322749376916",8,"Research & Report","ESA RN 21 Midterm Conference - Data quality in quantitative research","ESA RN 21 Midterm Conference centers on “Data quality in quantitative research,” focusing on methodological challenges that arise when comparing cross-cultural and longitudinal survey data. The program addresses risks such as comparing “apples with oranges,” and reviews both traditional tests for data comparability and newer approaches aimed at detecting or explaining (non-)invariance. It further examines measurement equivalence, nonequivalence handling strategies, and how SEM-based analyses can support meaningful cross-national comparisons.","ESA RN 21 Midterm Conference  \n“Data quality in quantitative research”  \nThursday, October 13rd  \n8:00– 9:00 Registration  \n9:00-9:15 Conference Opening  \nWolfgang Aschauer (ESA RN 21 coordinator)  \nSavvas Katsikides (Dean of Faculty Of Social Sciences And Education-University of Cyprus)  \nNektarios Partasides (President of the Cyprus Sociological Association)  \nIasonas Lamprianou (Local Organizer-University of Cyprus)  \n9:15-10:00 Keynote Eldad Davidov (University of Zürich, Switzerland)  \nChallenges in the analysis of cross-cultural data  \nI am going to begin with shortly discussing potential problems in the analysis of (particularly but not only survey) cross-cultural or longitudinal data, addressing in particular the risk of comparing ‘apples with oranges’ and possible sources for such problems. Next I will mention traditional statistical techniques to test for comparability of data across groups and expand them to newer methods suggested in the methodological literature to address potential (non-)comparability problems. These methods either identify or try to explain non-invariance. I will question whether some of them may eventually even solve non-comparability problems. Finally, I will relate this methodological discussion to recent suggestions especially in the political science literature to ignore problems of non-comparability, its background and the dangers associated with such a strategy when trying to conduct a meaningful analysis of comparative data.  \nChair: Wolfgang Aschauer (University of Salzburg, Austria)  \nAnna Domaranska  \nNational Academy of Sciences of Ukraine, Institute of Sociology, Kiev, Ukraine [anna_doma@list.ru](anna_doma@list.ru)  \nTesting the measurement equivalence in cross-cultural research:  \nAddress the problem of nonequivalence  \nIt’s common knowledge that supporting the presence of equivalence is an absolute necessity for meaningful international comparison. However testing the measurement equivalence can be highly problematic when applied to widely diverse cultural groups. According to B. Byrne,  \nF. van de Vijver (2010) the assumption that all samples derive from the same population is violated as participating countries of survey projects represent different parts of the world. Also modification indices, which usually work well for detecting sources of nonequivalence with a small number of groups, are performing badly when the number of groups is large and diverse. Despite notable progress in the subject field, it is highly likely to encounter evidences of nonequivalence the nature of which is unclear. Thus a key question arises what can be done when equivalence is not supported by the data?  \nSo far the literature suggests several strategies to deal with measurement nonequivalence. Firstly, partial invariance is regarded as acceptable when at least two indicators per construct are equal across groups. Secondly, finding the groups of countries where measurement equivalence holds or clustering countries in some meaningful manner for instance according to affluence, religion, global region, important contextual variables or use an established classification system. Lastly, trying to explain the absent of equivalence by means of a multiple indicators multiple causes (MIMIC) model or a multilevel structural equation modelling (MLSEM) (Byrne & van de Vijver, 2010; Davidov et al. 2012; Davidov et al. 2014) .  \nThe purpose of this study is discussing and illustrating these strategies in order to find optimal sequence of research steps for conducting the meaningful comparison in cross-national studies. Based on the ISSP Social Inequality Module collected in 2009 within 38 countries, multiple group confirmatory factor analysis (MGCFA) has been used for testing the measurement equivalence.  \nMagdalena Burdach Jolanta Perek-Białas  \nWarsaw School of Economics/Jagiellonian University, Kraków, Poland [jperek@sgh.waw.pl](jperek@sgh.waw.pl)  \nEvaluation of using SEM in analysis of relations between tru","cbCaiamBzJL9fCji","https://ap.wps.com/l/cbCaiamBzJL9fCji","pdf",1244626,1,43,"English","en",105,"# ESA RN 21 Midterm Conference\n## Conference opening\n## Keynote: Challenges in the analysis of cross-cultural data\n## Testing the measurement equivalence in cross-cultural research\n## Evaluation of using SEM in analysis of relations between trust and public institutions' performance\n## Social uses of the Internet: structured data analysis","[{\"question\":\"What main problem does the keynote highlight for cross-cultural quantitative research?\",\"answer\":\"It highlights difficulties in analyzing cross-cultural and longitudinal data, especially the risk of comparing non-equivalent measures and the sources of non-comparability.\"},{\"question\":\"Why is testing measurement equivalence considered problematic across diverse cultural groups?\",\"answer\":\"Because assumptions like all samples coming from the same population may be violated, and methods such as modification indices can perform poorly when group diversity and the number of groups are large.\"},{\"question\":\"What strategies does the program mention when measurement equivalence is not supported by the data?\",\"answer\":\"It discusses partial invariance, identifying/clustering groups where equivalence holds, and using models such as MIMIC or multilevel structural equation modeling to explain absent equivalence.\"}]","ESA RN 21 Midterm Conference - Data quality in quantitative research | PDF",1788051069,108,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"esa-rn-21-midterm-conference-data-quality-in-quantitative-research","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/esa-rn-21-midterm-conference-data-quality-in-quantitative-research/160156/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-30",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What main problem does the keynote highlight for cross-cultural quantitative research?","Question",{"text":75,"@type":76},"It highlights difficulties in analyzing cross-cultural and longitudinal data, especially the risk of comparing non-equivalent measures and the sources of non-comparability.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Why is testing measurement equivalence considered problematic across diverse cultural groups?",{"text":80,"@type":76},"Because assumptions like all samples coming from the same population may be violated, and methods such as modification indices can perform poorly when group diversity and the number of groups are large.",{"name":82,"@type":73,"acceptedAnswer":83},"What strategies does the program mention when measurement equivalence is not supported by the data?",{"text":84,"@type":76},"It discusses partial invariance, identifying/clustering groups where equivalence holds, and using models such as MIMIC or multilevel structural equation modeling to explain absent equivalence.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]