Affiliation:
1. George Mason University
2. Tulane University
Abstract
Previous research has suggested that there exists a bias in the social sciences against no-effect hypotheses. This is regrettable given the importance of establishing not only when an effect does occur but also the boundary conditions of that effect. The purposes of this article are two-fold The first purpose is to review relevant portions of the history of hypothesis testing in an attempt to identify the sources of bias against hypotheses of no effect. The second purpose is to develop and describe rigorous methods for providing evidence in support of no-effect hypotheses-methods that avoid some of the problems traditionally associated with no-effect conclusions.
Subject
Management of Technology and Innovation,Strategy and Management,General Decision Sciences
Cited by
100 articles.
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