When analyzing results it happens (quite often) that some participants are speeders or give… lets say creative answers and needed to be excluded.
How do you mark them?
You can mark them quickly as “Disqualified” and “Complete” but both is not right:
- Complete: Yes, they might have completed but are useless – would be a bias if we count them as Completed
- Disqualified: A participant that does not fit to the screener criteria disqualified, but that is different to the useless participants
How to differ and easily mark such participants?
Do we need to use a custom tag? That would not be included in a report within the completion rates (completion type)
I’d love it if there was some way of doing this within SG, but I think everyone has slightly different rules/criteria for data cleaning. I end up exporting data in Excel, flagging records I want to exclude (based on rules such as speeding, straight-lining, contradictory responses, and then (together with unique identifier) uploading the data to SPSS or Q and excluding the flagged records.
To manually quarantine a specific response: click on the survey, then go to the RESULTS tab. Click on a specific response you with to quarantine.
Click on the DATA QUALITY tab (within the response), at the upper right corner there is a drop down with “Select an Action”, select Quarantine.
Hi all – in this same line of discussion – I have a methodological/theory question for other people in my field. What do you do if you suspect that a handful of people didn’t fully read a response option – and their answers are actually incorrect? Especially if subsequent responses demonstrate they answered the one question wrong. Do you just ignore it – and report data that is probably incorrect? Do you delete their answer to the question you think they misreported? What is your policy? Thoughts?
SurveyGizmo has a Data Cleaning tool that sounds like it might be what you are looking for. Take a look at the documentation here:
This tool allows you to ‘quarantine’ responses rather than ‘disqualifying’ them.
Hope this helps!