I am working with data collected on the MTurk platform that links directly to a Qualtrics survey. The data is easy to format, so there's not a lot of wrangling there.
I have many questionnaires with different lengths, all of which have Cronbach's alpha of over .7 and most are in the high .88-.97 range. I have control questions in my surveys to screen out bots and participants who are not conscientious responders.
On questionnaire using a Likert scale from 1-5, I know it's possible to get good alphas if someone responds with all 1, someone responds all 2, someone responds all 3, etc. I'm curious if anyone knows of a package or method for identifying these "flatliners" either quantitatively or possibly visually if you could think of how to plot this using a heatmap. Ideally, you could tell if someone was a flatline because their data would look more like Tetris blocks if colored in rather than confetti. Does this make sense?