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Random Factors in ANOVA

Sally Jackson & Dale E. Brashers

Pub. date: 1994 | DOI: http://dx.doi.org/10.4135/9781412985567

Print ISBN: 9780803950900 | Online ISBN: 9781412985567

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STATISTICAL ASSUMPTIONS

F tests in the analysis of variance depend on assumptions made about the terms entering into the numerator and denominator of the F statistic. The assumptions are necessary in order to derive the distribution of the F statistic. This does not necessarily mean that the test is valueless if the assumptions are not met, for it is often the case that even though the assumptions are necessary to derive the distribution at a theoretical level, a close fit with the assumptions is not necessary to approximate the theoretical distribution at a practical level. As we will see, the assumptions associated with random effects in analysis of variance can be quite complicated and difficult to evaluate. Hence, it is wise to begin by asking how these assumptions are to be taken. Do they limit the use of random effects analysis to a very special set of cases in which the assumptions ...

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