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Data sharing policy

(2014-Apr-09, 09:59:21)Duxide Wrote: Then even non appointed reviewers can request the file to be sent via email. At least the author wary of conflict of interests will have proof (email).

That's a good option. Also emil, I don't think you need to be too stringent with the data sharing. The author can also publish the covariance matrix (+ variance, Mean, SD). With that, the reviewers can use them and replicate the results. Even this is really an improvement. If you look at most studies in other journals, you don't see the covariance matrix reported. Apparently it's not obligatory. But it's a defect. Several times, in meta-analyses, the author(s) mention in their inclusion criteria that they select data for which they have the variance/covariance matrix.

By the way, I remember 2 times when I asked data (by mail) to some authors. I knew they wouldn't give me the raw data, so I asked only for the correlation (or covariance, or both) matrix. I have been told by them that the data do not belong to them and that even this is not possible. Once, I have been told that they don't have the data.
As mentioned in his paper, Wicherts did a study where they found that there was a correlation between authors being reluctant to share datasets and statistics errors in papers they had written. Extreme bad for science.
Stats error is unlikely to go undetected by reviewers if the "input data" (e.g., covariance matrix) is reported. The only little disadvantage in it is if the author itself misreported the numbers that appear on the input data.

If you do PCA, path analysis, or multivariate genetic analyses by way of DF regressions, for example, just having the covariance (or the cross-twin covariance for genetic analyses) is sufficient to ensure that you can replicate the same numbers that appear in the submitted paper.
I talked with Meng Hu about what to do when the raw data isn't available, but some summary data is which is what the researcher used. This is the case for an upcoming submission s/he is working on.

My answer is that the data sharing policy requires that the data the researcher used be made available. If the researcher only used summarized data, then there is no requirement of making the inaccessible raw data available.

Does that seem reasonable?

For instance, if a researcher found a study with a correlation matrix and used that for factor analysis. The data sharing policy would require the correlation matrix be published/attached, but would not require the raw data to be published, which might of course be unavailable to the researcher.
I don't think John is planning to do a factor analysis, and I don't see the option for doing it, in the NCES database we use. We only make tabulations. Thus, the only thing we can do is to add a supplementary paper in which we illustrate the procedure, with screenshots, like the ones I sent you before. We can also put some screenshots of the numbers generated by the tabulations, as an example, but I don't think we will insert all of them. There are too many tables.
This is fine with me. I think the other reviewers will agree.
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