Abstract
Recall that in significance testing we observe data and propose as a null hypothesis a statistical model that could have generated such data, lacking a treatment effect. We then calculate the probability of the observed data. If that probability is very low, we conclude that the null hypothesis is in adequate to describe how the data were generated. To calculate the probability, we consider a set of possible observations:
The data we observed plus all possible patterns of data that would have been “more extreme” than these data.
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© 1992 Springer-Verlag New York, Inc.
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Salsburg, D.S. (1992). Permutation Tests and Resampling Techniques. In: The Use of Restricted Significance Tests in Clinical Trials. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4414-1_9
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DOI: https://doi.org/10.1007/978-1-4612-4414-1_9
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-8762-9
Online ISBN: 978-1-4612-4414-1
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