Closed testing procedure

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In statistics, the closed testing procedure [1] is a general method for performing more than one hypothesis test simultaneously.

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[edit] The closed testing principle

Suppose there are k hypotheses H1,..., Hk to be tested and the overall type I error rate is α. The closed testing principle allows the rejection of any one of these elementary hypotheses, say Hi, if all possible intersection hypotheses involving Hi can be rejected by using valid local level α tests. It controls the familywise error rate for all the k hypotheses at level α in the strong sense.

[edit] Example

Suppose there are three hypotheses H1,..., H3 to be tested and the overall type I error rate is 0.05. Then H1 can be rejected at level α if H1 ∩ H2 ∩ H3, H1 ∩ H2, H1 ∩ H3 and H1 can all be rejected using valid tests with level 0.05.

[edit] Special cases

The Holm-Bonferroni method is a special case of a closed test procedure for which each intersection null hypothesis is tested using the simple Bonferroni test. As such, it controls the familywise error rate for all the k hypotheses at level α in the strong sense.

[edit] References

  1. ^ Marcus R, Peritz E, Gabriel KR (1976): "On closed testing procedures with special reference to ordered analysis of variance", Biometrika 63: 655-660

[edit] See also