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Advisor(s)
Abstract(s)
Analysis of variance (ANOVA) is one of the most frequently used statistical analyses in
several research areas, namely in medical research. Despite its wide use, it has been applied
assuming that sample dimensions are known. In this work we aim to carry out ANOVA
like analysis of one-way fixed effects models, to situations where the samples sizes may
not be previously known. In these situations it is more appropriate to consider the sample
sizes as realizations of independent random variables. This approach must be based on
an adequate choice of the distributions of the samples sizes. We assume the Poisson
distribution when the occurrence of observations corresponds to a counting process. The
Binomial distribution is the proper choice if we have observations failures and there exist
an upper bound for the sample sizes. We also show how to carry out our main goal by
computing correct critical values. The applicability of the proposed approach is illustrated
considering a real data example on cancer registries. The results obtained suggested that
false rejections may be avoided by applying our approach.
Description
Keywords
ANOVA Random sample sizes Fixed effects models Correct critical values Cancer registries