![]() ![]() If you can't keep track of your dataset, that makes me worry about the whole analysis. So I suspected that the authors had more than one version of their dataset running around. I was reviewing one paper where the numbers in a table and figure should have been identical, but they didn't match. This may result from sloppy cutting and pasting or because authors redo an analysis, but maybe they forget to update the entire manuscript. For example, I've seen a lot of papers where the abstract reports different numbers than the body of the paper. I see numerical inconsistencies a lot when I'm reviewing papers. But if a reviewer or editor sees this kind of inconsistency, it raises a lot of red flags. Maybe they meant to say that they had a maximum follow up of two years or that they aim to follow participants for two years. Clearly, the average follow-up can't be one and a half years if the minimum follow-up is two years. I was editing somebody's work and in the method section they said, "We followed participants for a minimum of two years." But in the results section, they said that the follow up time, "The average follow-up time was one and a half years". Checking for consistency means making sure that you don't have things that are contradictory in different places in the manuscript. You also want to make sure that your references are not what I call, references to nowhere. ![]() Before you submit your final draft, you should check for consistency and, in particular, for numerical consistency. Once the prose is sounding good, there are a few other things that I want to make sure you check. ![]() There's a checklist that you should go through. In this last module, I want to give you a few last tips for your very final draft before you send something off to your editor or to a journal. ![]()
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