Do Top Journals Require Reporting on Missing Data Techniques?

by Karen Grace-Martin


Q: Do most high impact journals require authors to state which method has been used on missing data?

I don’t usually get far enough in the publishing process to read journal requirements.

But based on my conversations with researchers who both review articles for journals and who deal with reviewers’ comments, I can offer this response.

I would be shocked if journal editors at top journals didn’t want information about the missing data technique.  If you leave it out, they’ll either assume you didn’t have missing data or are using defaults like listwise deletion.

I’m sure there are some fields or research areas in which not having missing data isn’t a possibility, so they’re going to want an answer.

And if you’re using a technique that’s better than listwise deletion, go ahead and tell them.  While not all editors may be caught up with the state of the art in missing data, editors at top level journals should be.

If your editors or reviewers aren’t caught up with new missing data techniques, and think you’re trying to pull a fast one, cite liberally. You may have to educate reviewers a bit.   There are a number of published articles in many fields on the benefits of the newest techniques.

Here are a few good ones.  If you know of others, please feel free to leave them in the comments.


This post is part of a series of answers about missing data that I was asked during a recent webinar.  There were nearly 300 people on the live webinar, so we didn’t get through all the questions.  So I’m answering some of the ones we missed here.

To see the full list of posts in this series, and a whole lot more, visit our Missing Data page.

tn_ircWant to learn more about how to handle Missing Data? In this 5-part workshop, you’ll learn all about two fabulous modern missing data techniques: multiple imputation and maximum likelihood.

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