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In
statistics Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of ...
, the Šidák correction, or Dunn–Šidák correction, is a method used to counteract the problem of
multiple comparisons In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously or infers a subset of parameters selected based on the observed values. The more inferences ...
. It is a simple method to control the
familywise error rate In statistics, family-wise error rate (FWER) is the probability of making one or more false discoveries, or type I errors when performing multiple hypotheses tests. Familywise and Experimentwise Error Rates Tukey (1953) developed the concept of ...
. When all null hypotheses are true, the method provides familywise error control that is exact for tests that are stochastically independent, is conservative for tests that are positively dependent, and is liberal for tests that are negatively dependent. It is credited to a 1967 paper by the
statistician A statistician is a person who works with theoretical or applied statistics. The profession exists in both the private and public sectors. It is common to combine statistical knowledge with expertise in other subjects, and statisticians may wor ...
and probabilist
Zbyněk Šidák Zbyněk Šidák (24 October 1933 – 12 November 1999) was a Czech mathematician. He is known for developing the Šidák correction. Early life and education Šidák was born and raised in Golčův Jeníkov. He completed his undergraduate studie ...
.


Usage

* Given ''m'' different null hypotheses and a familywise alpha level of \alpha, each null hypotheses is rejected that has a p-value lower than \alpha_ = 1-(1-\alpha)^\frac . * This test produces a familywise Type I error rate of exactly \alpha when the tests are independent from each other and all null hypotheses are true. It is less stringent than the Bonferroni correction, but only slightly. For example, for \alpha = 0.05 and ''m'' = 10, the Bonferroni-adjusted level is 0.005 and the Šidák-adjusted level is approximately 0.005116. * One can also compute
confidence intervals In frequentist statistics, a confidence interval (CI) is a range of estimates for an unknown parameter. A confidence interval is computed at a designated ''confidence level''; the 95% confidence level is most common, but other levels, such as 9 ...
matching the test decision using the Šidák correction by using 100(1 − α)1/''m''% confidence intervals. * For continuous problems, one can employ
Bayesian Thomas Bayes (/beɪz/; c. 1701 – 1761) was an English statistician, philosopher, and Presbyterian minister. Bayesian () refers either to a range of concepts and approaches that relate to statistical methods based on Bayes' theorem, or a followe ...
logic to compute m from the prior-to-posterior volume ratio.


Proof

The Šidák correction is derived by assuming that the individual tests are
independent Independent or Independents may refer to: Arts, entertainment, and media Artist groups * Independents (artist group), a group of modernist painters based in the New Hope, Pennsylvania, area of the United States during the early 1930s * Independ ...
. Let the significance threshold for each test be \alpha_1; 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 - \alpha_1)^m. Our intention is for this probability to equal \alpha, the significance level for the entire series of tests. By solving for \alpha_1, we obtain \alpha_1 = 1 - (1 - \alpha)^.


Šidák correction for t-test


See also

*
Multiple comparisons In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously or infers a subset of parameters selected based on the observed values. The more inferences ...
*
Bonferroni correction In statistics, the Bonferroni correction is a method to counteract the multiple comparisons problem. Background The method is named for its use of the Bonferroni inequalities. An extension of the method to confidence intervals was proposed by Oliv ...
*
Familywise error rate In statistics, family-wise error rate (FWER) is the probability of making one or more false discoveries, or type I errors when performing multiple hypotheses tests. Familywise and Experimentwise Error Rates Tukey (1953) developed the concept of ...
* Closed testing procedure


References


External links


The Bonferonni and Šidák Corrections for Multiple Comparisons
{{DEFAULTSORT:Sidak correction Multiple comparisons