THE EFFECTS OF THE VIOLATION OF ERROR'S
INDEPENDENCE HYPOTHESIS IN TWO-WAY MODELS.
Luiz Carlos BAIDA[1]
Antonio Francisco IEMMA[2]
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ABSTRACT:
This is a study of the implications induced by violation of the independence
assumptions of types I and II errors probabilities, inherent to classical
hypothesis in the linear models with fixed and balanced two factors, analyzed
under the standard structure of Gauss-Markov's linear models. The theory is
developed in an appropriate form, studing three equicorrelation cases of the
errors of the model. Tables of the errors probabilities are given to show the
bias that appears when the standard model is used inadequately. To produce
these tables we have considered various values of the level of the factors, the
size of the samples, the involved correlations and finally, the pre-fixed
nominal level of the significance (( = 0,05).
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KEYWORDS:
Types I and II errors probabilities; analysis of variance; dependent errors;
equicorrelation.