This is a hypothesis test designed to be correctly sized in that the probability of rejecting the null when it is true will be equal to your alpha level. Other than that it is a pretty useless test mainly intended for when people say something like "I just need a p-value".
SnowsCorrectlySizedButOtherwiseUselessTestOfAnything(x,
data.name = deparse(substitute(x)),
alternative = "You Are Lucky", ..., seed)The data, or nothing, or something equally irrelevant
The name of the data for the output
The phrase for the alternate hypothesis in the output
Additional arguments that will be silently ignored (like
x), future versions may mockingly ignore these instead
A seed (numeric or character) used to seed the random number generator. Use this or manually set the seed if you want reproducible (but still meaningless) results
An object of class htest with the following elements:
The p-value
The test statistic (identical to the p-value)
The name of the data (if any)
The name of the test
a phrase representing the alternative hypothesis
optionally the seed that was used
Some of the advantages/disadvantages of this test include:
The probability of a Type I error is alpha
Power can be easily computed (it is alpha)
Power is independent of the sample size
Power is independent of the hypotheses
This test is not affected by missing data (present data either)
This test does not depend on any distributional or independence assumptions
The author is unlikely to be willing to publish in any "journal" that would be willing to publish this test.
fortune(264)
# NOT RUN {
SnowsCorrectlySizedButOtherwiseUselessTestOfAnything(log(rnorm(100)))
# }
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