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I’ve signed up to it Documentation pn QAmyDta is truly horrible On 15 Nov 2019, at 09:53, Peter Watson <[log in to unmask]<mailto:[log in to unmask]>> wrote: Hi everyone, Please find details below of a webinar from the UK Data Service which describes a tool to check the quality of their health data (which is in SPSS format and hence of possible interest to us SPSS users) and could we think be used to check other data sets. If anyone knows of any similar tools or has experience of using the QAMyData tool do feel free to share. Laurie is particularly interested to hear from any group members and his e-mail address is below. Many thanks Peter ---------------------------------------------------------------------------------------- Peter Watson MRC Cognition & Brain Sciences Unit University of Cambridge 15 Chaucer Road Cambridge CB2 7EF Telephone: +44 (0) 1223 766166 x69479 or +44 (0) 1223 769479 (direct) Fax +44 (0) 1223) 359062 From: Laurence Moseley <[log in to unmask]<mailto:[log in to unmask]>> Sent: 14 November 2019 12:25 To: Peter Watson <[log in to unmask]<mailto:[log in to unmask]>> Subject: FW: Webinar: Introduction to QAMyData 'health-check' tool for numeric data I have just received this email and circulated it my own local mailing list. However, given its discussion of a data quality checking tool which is applicable to SPSS and other packages, I thought that it might be of more general interest to ASSESS and allied members, which is why I am forwarding it to you. My note to our local mailing list read “This looks as though it could be very useful, both for those of us who are often analysing research data, and particularly for our students – who need to develop good habits from the beginning. I suspect that it could be 50 minutes well spent. In my own consultancy work, much of the time (often the majority) has been taken up tidying up other peoples’ data prior to the actual analysis, and this tool, if it does what it says on the tin, should help in that endeavour. The fact that it appears to work for SPSS, Stata, and SAS formats (as well as more general ones like CSV) might make it more widely useful. However, this tool is new to me, so I would welcome any reliable information. If any member of the group knows of, and can recommend, any similar tool, I would be grateful if they could let me know what it is called and where it can be located. The only similar ones that I have used in the past have been GritBot and the Missing Values Analyses elements in SPSS, but, although useful, they solved only part of the problem.” If you, too, have any suggestions for similar, or better, solutions, I would be grateful if you could let me know. If you sit through the webinar, I hope that it proves useful. Incidentally, if you register for the webinar, but cannot make the live presentation, they usually send you a recording so that you can watch it later. Cheers Laurie 14th November 2019 From: UK Data Service News <[log in to unmask]<mailto:[log in to unmask]>> On Behalf Of Gillian Meadows Sent: 14 November 2019 08:26 To: [log in to unmask]<mailto:[log in to unmask]> Subject: Webinar: Introduction to QAMyData ‘health-check’ tool for numeric data Webinar: Introduction to QAMyData ‘health-check’ tool for numeric data 2 December 2019 Online, 15.00 - 16.00 GMT This free webinar is an introduction to the new QAMyData tool for health-checking your numeric data, recently launched in November 2019. The tool uses automated methods to detect and report on some of the most common problems found in survey or numeric data, such as missingness, duplication, outliers and direct identifiers. The open source tool helps data creators and users quality assess a numeric data file using a comprehensive list of ‘tests’, classified into types: file, metadata, data integrity, and direct identifiers. Popular file formats can be tested, including SPSS, Stata, SAS and CSV. The test configuration feature allows the creation of your own unique Data Quality Profile, that can play a useful role in your ‘FAIR’ data checking. The webinar will describe the tests that are included in the tool, how to configure these to meet your own quality thresholds, and how to download the software from our Github page. We will also show our teaching exercise using messy data that can help promote data management skills. The webinar will consist of a 30 minute presentation followed by 20 minutes for questions. Presenters: Louise Corti, Cristina Magder and Myles Offord Level: Intermediate Experience/knowledge required: Some knowledge of survey or numeric data Target audience: Data publishers/data archivists, users of numeric data, peer reviewers of data, quantitative research lecturers Booking<https://www.ukdataservice.ac.uk/news-and-events/eventsitem/?id=5548> ___________________________________________ Gill Meadows Administrator, User Support and Training ___________________________________________ E [log in to unmask]<mailto:[log in to unmask]> W ukdataservice.ac.uk<http://ukdataservice.ac.uk/> ___________________________________________ UK Data Service Cathie Marsh Institute for Social Research University of Manchester W http://www.socialsciences.manchester.ac.uk/ ___________________________________________ Legal Disclaimer: Any views expressed by the sender of this message are not necessarily those of the UK Data Service. This email and any files with it are confidential and intended solely for the use of the individual(s) or entity to whom they are addressed. 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