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Significance testing with no alternative hypothesis: a measure of surprise

By J. V. Howard


A pure significance test would check the agreement of a statistical model with the observed data even when no alternative model was available. The paper proposes the use of a modified p-value to make such a test. The model will be rejected if something surprising is observed (relative to what else might have been observed). It is shown that the relation between this measure of surprise (the s-value) and the surprise indices of Weaver and Good is similar to the relationship between a p-value, a corresponding odds-ratio, and a logit or log-odds statistic. The s-value is always larger than the corresponding p-value, and is not uniformly distributed. Difficulties with the whole approach are discussed

Topics: HA Statistics
Publisher: Springer
Year: 2009
DOI identifier: 10.1007/s10670-008-9148-4
OAI identifier:
Provided by: LSE Research Online
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