[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-647738-105":59,"doc-detail-647738-en":129},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":122,"head_meta":124,"extra_data":126,"updated_unix":128},105,"en","secondary-analysis-of-large-national-survey-datasets-methodological-issues","Secondary analysis of large national survey datasets - Methodological issues","","This paper examines methodological issues involved in secondary analysis of large national survey datasets for nursing research. Sampling, data collection, non-response, and missing data are evaluated in relation to methodological validity and reliability. Reanalyzing such datasets offers an expedient, cost-efficient route to generate nursing knowledge, yet successful studies require careful attention to intrinsic limitations. Nursing researchers are urged to understand potential errors and their influence on analytic results, even though elimination of all error is impossible.",{"@graph":69,"@context":121},[70,84,104],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/secondary-analysis-of-large-national-survey-datasets-methodological-issues/647738/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":98,"encodingFormat":97,"isAccessibleForFree":99,"interactionStatistic":100},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/secondary-analysis-of-large-national-survey-datasets-methodological-issues/647738.png","ImageObject",300,407,{"name":92,"@type":93},"Olivia Brown","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23",true,{"@type":101,"interactionType":102,"userInteractionCount":4},"InteractionCounter",{"@type":103},"ViewAction",{"@type":105,"mainEntity":106},"FAQPage",[107,113,117],{"name":108,"@type":109,"acceptedAnswer":110},"What is the focus of this paper on secondary analysis of survey datasets?","Question",{"text":111,"@type":112},"The paper focuses on methodological issues related to conducting secondary analysis of large national survey datasets, emphasizing validity and reliability concerns.","Answer",{"name":114,"@type":109,"acceptedAnswer":115},"Which methodological areas are discussed as potential sources of error?",{"text":116,"@type":112},"Key areas include survey sampling, data collection, non-response, and missing data, each linked to threats to validity and reliability.",{"name":118,"@type":109,"acceptedAnswer":119},"Why do nursing researchers need to consider limitations before analyzing existing survey data?",{"text":120,"@type":112},"Because researchers did not participate in the original study design, data collection, or data entry, understanding dataset limitations is necessary to judge accuracy and the potential impact of errors on results.","https://schema.org",{"og:url":83,"og:type":123,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":125,"canonical":83},"index,follow",{"doc_id":127,"site_id":62},647738,1792789977,{"code":4,"msg":5,"data":130},{"doc_id":127,"user_id":131,"nickname":92,"user_avatar":132,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":4,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":29,"language":138,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":139,"faqs":140,"seo_title":141,"seo_description":67,"update_tm":128,"read_time":142},16904993612988,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","Japan Journal of Nursing Science (2013) 10, 130–135 doi:10.1111/j.1742-7924.2012.00213.x  \nMETHODOLOGICAL ARTICLE  \nSecondary analysis of national survey datasets  \nSunjoo BOO1 and Erika Sivarajan FROELICHER1,2  \nDepartments of 1 Physiological Nursing and 2 Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California, USA  \nAbstract  \nAim: This paper describes the methodological issues associated with secondary analysis of large national survey datasets.  \nMethods: Issues about survey sampling, data collection, and non-response and missing data in terms of methodological validity and reliability are discussed.  \nResults: Although reanalyzing large national survey datasets is an expedient and cost-efficient way of producing nursing knowledge, successful investigations require a methodological consideration of the intrinsic limitations of secondary survey analysis.  \nConclusions: Nursing researchers using existing national survey datasets should understand potential sources of error associated with survey sampling, data collection, and non-response and missing data. Although it is impossible to eliminate all potential errors, researchers using existing national survey datasets must be aware of the possible influence of errors on the results of the analyses.  \nKey words: data collection/methods, data interpretation, nursing research/methods, reproducibility of results, research design, statistical.  \nINTRODUCTION  \nAdvances in digital technology have made it possible to have easy access to large datasets and to analyze them with personal computers. In response, secondary data analysis has become commonly recognized as a legitimate form of scientific inquiry in nursing research (Kneipp & Yarandi, 2002) . Simply defined, secondary data analysis is the method of using any existing datasets (Clarke & Cossette, 2000) . Particularly, at a time of limited funding for non-experimental studies, secondary data analysis can be an alternative means to be able to conduct studies with less cost. It is an expedient and cost-effective way of producing knowledge, especially when it involves a nationally representative database. Large national surveys on behaviors, health, or healthcare commonly contain multiple variables important to  \nCorrespondence: Sunjoo Boo, Department of Physiological Nursing, University of California San Francisco, San Francisco, CA 94143-0610, USA.  \nEmail: [sunjoo.boo@gmail.com](sunjoo.boo@gmail.com)  \nReceived 1 December 2011; accepted 26 March 2012 .  \nnursing research and practice (Bibb & Sandra, 2007; Bierman & Bubolz, 2003; Kneipp & Yarandi, 2002) . Analysis of these representative data not only provides reliable national estimates but also offers the opportunity to test or generate nursing theories based on a large representative sample.  \nWhile the benefits of reanalysis of national survey datasets are considerable, several limitations need to be considered. Because researchers using existing survey datasets were not involved in the study or sampling design, data collection, or the data entry process, it is important to fully understand the accuracy of the datasets before delving into the database. Without a full understanding of the limitations or complexities of the analysis of large national survey datasets, the process will be challenging and the results may be unreliable. Researchers planning to analyze national survey datasets must recognize unique issues pertinent to survey data quality at the beginning so that the potential for introducing threats to reliability and validity can be addressed and their impact on the results considered.  \n© 2012 The Authors  \nJapan Journal of Nursing Science © 2012 Japan Academy of Nursing Science  \nJapan Journal of Nursing Science (2013) 10, 130–135 Secondary analysis of survey data  \nPreviously, several articles have covered a wide range of topics in terms of general theoretical (Clarke & Cossette, 2000), methodological (Castle, 2003; Clarke &","cbCaiaDIov8Qqeyh","https://ap.wps.com/l/cbCaiaDIov8Qqeyh","pdf",109975,"English","# Introduction\n## Defining secondary data analysis and benefits\n## Key limitations to consider\n# Making good use of existing survey data\n## Data access, ethics, and IRB considerations\n## Nationally representative datasets and nursing research uses","[{\"question\":\"What is the focus of this paper on secondary analysis of survey datasets?\",\"answer\":\"The paper focuses on methodological issues related to conducting secondary analysis of large national survey datasets, emphasizing validity and reliability concerns.\"},{\"question\":\"Which methodological areas are discussed as potential sources of error?\",\"answer\":\"Key areas include survey sampling, data collection, non-response, and missing data, each linked to threats to validity and reliability.\"},{\"question\":\"Why do nursing researchers need to consider limitations before analyzing existing survey data?\",\"answer\":\"Because researchers did not participate in the original study design, data collection, or data entry, understanding dataset limitations is necessary to judge accuracy and the potential impact of errors on results.\"}]","Secondary analysis of large national survey datasets - Methodological issues | PDF",15]