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Three Roles for Statistical Significance and the Validity Frontier in Theory Testing

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dc.contributor.author Lee, Allen
dc.contributor.author Mohajeri, Kaveh
dc.contributor.author Hubona, Geoffrey
dc.date.accessioned 2016-12-29T02:07:26Z
dc.date.available 2016-12-29T02:07:26Z
dc.date.issued 2017-01-04
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41854
dc.description.abstract This study offers a method for empirically testing theories operationalized in the form of multivariate statistical models. An innovation of the method is that it distinguishes testing into three separate forms, “effect testing,” “prediction testing,” and “theory testing,” where statistical significance plays a separate role in each one. In another innovation, the researcher specifies not only his or her desired level of statistical significance, but also his or her desired level of practical significance. Statistical significance and practical significance each serve as a dimension in a two-dimensional table that specifies the rejection region – the region where the researcher can justify the decision to reject the theory being tested. The boundary of the rejection region is the “validity frontier,” which ongoing research may advance so as to reduce the size of the rejection region.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject theory testing
dc.subject hypothesis testing
dc.subject statistical significance
dc.subject practical significance
dc.subject rejection region
dc.title Three Roles for Statistical Significance and the Validity Frontier in Theory Testing
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2017.691
Appears in Collections: Theory and Information Systems Minitrack


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