Summary
In random analysis of variance one uses the statistic MSA/MSAB to test the hypothesis that ‘factor A has no effect’. Here the wrong test, using MSA/MSE as statistic, is compared with the usual test. The two tests do, of course, test two different hypotheses. An analysis of the employed terminology reveals that the wrong hypothesis is not ‘worse’ than the usual hypothesis. It is analogous to the corresponding hypothesis in fixed analysis of variance. Because of that, and by power considerations, it is argued that the wrong test should be preferable in most applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anderson, R. L. (1960): Some remarks on the design and analysis of factorial experiments. In: I. O1kin et al., eds. Contributions to Probability and Statistics. Stanford Univ. Press, Stanford, 35–36.
Kempthorne, O. (1952): The design and analysis of experiments. J. Wiley, New York.
Scheffé, H. (1956): Alternative models for the analysis of variance. Ann. Math. Statist. 27, 251–271.
Yates, F. (1967): A fresh look at the basic principles of the design and analysis of experiments. Proc. Fifth Berkeley Symposium on Mathematical Statistics and Probability 4, 777–790.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1976 Springer Basel AG
About this chapter
Cite this chapter
Linhart, H. (1976). The Random Analysis of Variance Model and the Wrong Test. In: Ziegler, W.J. (eds) Contribution to Applied Statistics. Experientia Supplementum, vol 22. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-5513-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-0348-5513-6_15
Publisher Name: Birkhäuser, Basel
Print ISBN: 978-3-0348-5515-0
Online ISBN: 978-3-0348-5513-6
eBook Packages: Springer Book Archive