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

Lee, Allen; Mohajeri, Kaveh LU and Hubona, Geoffrey (2017) In Proceedings of the 50th Hawaii International Conference on System Sciences p.5737-5746
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... (More)
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 sizeof the rejection region. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
theory testing, hypothesis testing, statistical significance, practical significance, rejection region
in
Proceedings of the 50th Hawaii International Conference on System Sciences
pages
10 pages
publisher
Institute of Electrical and Electronics Engineers Inc.
ISBN
978-0-9981331-0-2
978-0-9981331-0-2
language
English
LU publication?
yes
id
dc669d50-fdd4-41e6-ac40-9f2923f2e9ac
alternative location
http://hdl.handle.net/10125/41854
date added to LUP
2017-02-23 17:26:15
date last changed
2017-11-14 09:55:13
@inproceedings{dc669d50-fdd4-41e6-ac40-9f2923f2e9ac,
  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 sizeof the rejection region.},
  author       = {Lee, Allen and Mohajeri, Kaveh and Hubona, Geoffrey },
  booktitle    = {Proceedings of the 50th Hawaii International Conference on System Sciences},
  isbn         = {978-0-9981331-0-2},
  keyword      = {theory testing,hypothesis testing,statistical significance,practical significance,rejection region},
  language     = {eng},
  month        = {01},
  pages        = {5737--5746},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  title        = {Three Roles for Statistical Significance and the Validity Frontier in Theory Testing},
  year         = {2017},
}