Difference between revisions of "Randomization Inference"
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Revision as of 20:21, 6 November 2017
Randomization inference is a statistical practice for calculating regression p-values that reflect the true source of variation in experimentally assigned data. When the researcher controls the treatment assignment of the entire observed group, that variation arises from the treatment assignment (rather than from the sampling strategy), and therefore p-values based on the randomization are more appropriate than "standard" p-values.