Abstract
For this chapter some knowledge of power equations is required. This is given in Chapter 7 of the first part of this title. Superiority testing of a study means testing whether the study meets its a priori defined expected power. Many therapeutic studies may be able to reject their null hypotheses, and, are, thus, statistically significant, but they do not meet their expected power. Although p-values are widely reported, power is rarely given in the report. This may be a problem in practice, since lack of power indicates that the treatments are less efficacious than expected. Superiority testing assesses whether the eventual power of a study is in agreement with the power as stated in the sample size calculation of the study.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 The Author(s)
About this chapter
Cite this chapter
Cleophas, T.J., Zwinderman, A.H. (2012). Superiority Testing Instead of Null Hypothesis Testing. In: Statistical Analysis of Clinical Data on a Pocket Calculator, Part 2. SpringerBriefs in Statistics. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4704-3_14
Download citation
DOI: https://doi.org/10.1007/978-94-007-4704-3_14
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4703-6
Online ISBN: 978-94-007-4704-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)