Abstract
In randomized controlled trials, prior to statistical analysis, the data are checked for outliers and erroneous data. Data-cleaning is defined as deleting-the-errors/maintaining-the-outliers. Statistical tests are, traditionally, not very good at distinguishing between errors and outliers. However, they should be able to point out main endpoint results that are closer to expectation than compatible with random sampling. For example, a difference from control of 0.000 is hardly compatible with random sampling. As it comes to well-balanced random sampling of representative experimental data, nature will be helpful to provide researchers with results close to perfection.
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Cleophas, T.J., Zwinderman, A.H. (2012). The Interpretation of the p-Values. In: Statistics Applied to Clinical Studies. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2863-9_10
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