4 ms·
>Over the course of this reanalysis, we detected an error in imputing missing values for the SGRQ, whereby the worst possible score (100) was incorrectly impute
by ImaCake 7y ago
>Over the course of this reanalysis, we detected an error in imputing missing values for the SGRQ, whereby the worst possible score (100) was incorrectly imputed for missing values of participants who had died beyond the 6-month study period. The correct approach would have been to classify those values as missing because those participants had not died by the 6 months after discharge study end point.
The reassignment error is possibly forgivable, but I think this second error should have been easier to catch and is much less easy to forgive. A simple filter check between possible score and some other status variable in the dataset would of caught this mistake. I am doing a Masters in Biostatistics and this kind of checking is being taught to us early on, I hope there is more focus on it later to help avoid mistakes like this.
- codetrotter 7y agoTrivial errors can slip through the cracks easily. For example, people sometimes misspell “would’ve” as “would of” even if they actually know that the latter spelling is actually incorrect. Pointing fingers is easy after the fact, but spotting every possible error all of the time – no one is able to do that. I’ve even made that very same spelling mistake you did a time or two myself even though I try really hard to be correct in spelling and in all aspects of grammar, and even though I am well aware that “would of” is just plain wrong. We all slip up, and sometimes we do so in embarrassing ways. Especially when we are lacking sleep or when we are otherwise exhausted.
- tomrod 7y agoExactly. The notion of "failing forward" is somewhat related here -- don't focus on the blame game when addressing honest mistakes. (Fraud is a different matter). Focus on rectifying then moving forward.
- tomrod 7y agoEven when following every protocol, everyone will screw up at some point. The authors' approach is the correct way to deal with a screw up in the academic/research context -- broad communication, transparent assessment of the mistake, eager explanation.