TRNA (cytidine32/uridine32-2'-O)-methyltransferase

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In statistics, the Šidák correction, or Dunn–Šidák correction, is a method used to counteract the problem of multiple comparisons. It is a simple and conservative method to control the familywise error rate when assuming that the individual tests are independent. It was published in 1967 [1] by the statistician and probabilist Zbyněk Šidák.[2]

Usage

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  • If the test statistics are independent then testing each hypothesis at level αSID=1−(1−α)1m is Sidak's multiple testing procedure.
  • This test is more powerful than Bonferroni but the gain is small, and the procedure is far less general than Bonferroni's since it requires independence.
  • The method may be used for the construction of a trapezoid joint Confidence Region for the mean and the variance of data obtained from a Normal Distribution, since these two parameters are independent.

Proof

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The Šidák correction is derived by assuming that the individual tests are independent. Let the significance threshold for each test be α1; then the probability that at least one of the tests is significant under this threshold is (1 - the probability that none of them are significant). Since it is assumed that they are independent, the probability that all of them are not significant is the product of the probabilities that each of them are not significant, or 1−(1−α1)n. Our intention is for this probability to equal α, the significance level for the entire series of tests. By solving for α1, we obtain α1=1−(1−α)1/n.

Example

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For example, to test two independent hypotheses on the same data at 0.05 significance level, instead of using a p value threshold of 0.05, one would use a stricter threshold equal to 1−0.95≈0.025. Notably one can derive valid confidence intervals matching the test decision using the Šidák correction by using 100(1 − α1/n)% confidence intervals.

The Bonferroni correction is a safeguard against multiple tests of statistical significance on the same data falsely giving the appearance of significance, as 1 out of every 20 hypothesis-tests is expected to be significant at the α = 0.05 level purely due to chance. Furthermore, the probability of getting a significant result with n tests at this level of significance is 1 − 0.95n (1 − probability of not getting a significant result with n tests).

Similarly, the Šidák correction gives a stronger bound than the Bonferroni correction, because, for n≥1, α/n≤1−(1−α)1/n. But the Šidák correction requires the additional condition of independence. Previously, because the Šidák correction requires fractional powers (i.e. roots), the computationally simpler Bonferroni correction was often preferred instead. Now, inasmuch as computing fractional powers is trivial, preference of the Bonferroni method is due in part to tradition or unfamiliarity with the Šidák method. Additionally, the results of the two methods are highly similar for conventional significance levels (between .01 and .10).

See also

References

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