In my job role I often work with other people's datasets, non-experts bring me clinical data and I help them to summarise it and perform statistical tests.

The problem I am having is that the datasets I am brought are almost always riddled with typos, inconsistencies, and all sorts of other problems. I am interested to know if other people have standard tests which they do to try to check any datasets that come in.

I used to draw histograms of each variable just to have a look but I now realise there are lots of horrible errors that can survive this test. For example, I had a repeated measures dataset the other day where, for some individuals, the repeated measure was identical at Time 2 as it was at Time 1. This was subsequently proved to be incorrect, as you would expect. Another dataset had an individual who went from being very severely disordered (represented by a high score) to being problem-free, represented by 0's across the board. This is just impossible, although I couldn't prove it definitively.

So what basic tests can I run on each dataset to make sure that they don't have typos and they don't contain impossible values?

Thanks in advance!

In my job role I often work with other people's datasets; non-experts bring me clinical data and I help them summarise it and perform statistical tests.

The problem I am having is that the datasets I am brought are almost always riddled with typos, inconsistencies, and all sorts of other problems. I am interested to know if other people have standard tests which they do to try to check any datasets that come in.

I used to draw histograms of each variable just to have a look but I now realise there are lots of horrible errors that can survive this test. For example, I had a repeated measures dataset the other day where, for some individuals, the repeated measure was identical at Time 2 as it was at Time 1. This was subsequently proved to be incorrect, as you would expect. Another dataset had an individual who went from being very severely disordered (represented by a high score) to being problem-free, represented by 0's across the board. This is just impossible, although I couldn't prove it definitively.

So what basic tests can I run on each dataset to make sure that they don't have typos and they don't contain impossible values?