Question around participant data inclusion
I’m aware that roughly the variable (i.e. matrix columns) inclusion threshold for missingness in continuous variables is 20%, however, is there a rough guide for missingness in participants (i.e. matrix rows)?
I’m working with clinical, biochemical and survey data, which is quite patchy as some participants didn’t complete the survey questions or refused blood draws.
Is a cut off of 50% of missingness for each participants acceptable?
For now I’m using this for PLS-DA and DIABOLO with just these kind of variables, but down the track we’ll be including other omics layers such as transcriptomics and rare and common variants.