Generalized p-value: Difference between revisions

Revision as of 17:07, 27 April 2011

Revision as of 22:58, 20 December 2011

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{{Expert-subject|statistics|date=March 2011}}

{{Primary sources|date=October 2010}}

In [[statistics]], a '''generalized p-value''' is an extended version of the classical [[p-value]], which except in a limited number of applications, provideprovides only approximate solutions.

Conventional statistical methods do not provide exact solutions to many statistical problems such as those arise in [[mixed model]]s and MANOVA, especially when the problem involves many [[nuisance parameter]]s. As a result, practitioners often resort to approximate statistical methods or [[Asymptotic theory (statistics)|asymptotic statistical methods]] that are valid only with large samples. With small samples, such methods often have poor performance <ref name=WE/>. Use of approximate and asymptotic methods may lead to misleading conclusions or may fail to detect truly [[Statistical significance|significant]] results from [[experiment]]s.