A Comparison of Different Methods for Estimating the Missing Value in Two-way ANOVA
In this study, we consider missing value problem in two-way ANOVA model under the non-normal error terms, namely long-tailed symmetric (LTS) distribution. We obtain estimators of the missing value by using two different methodologies. First, iteratively reweighting algorithm (IRA) is used to compute the maximum likelihood (ML) estimate of the missing value. Second, the modified maximum likelihood (MML) methodology is used to obtain the explicit estimator of the missing value. In the simulation study, we compare the efficiencies of the proposed estimators with the traditional least squares (LS) estimator. We also show the effects of the proposed estimators on the efficiencies of the estimators of the model parameters. We illustrate the estimation methods on a real life example taken from the literature at the end of the study.
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