| Summary: | Classical parametric test such as ANOVA often used in testing the equality of central tendency since this method provide a good control of Type I error and generally more powerful than other statistical methods.However,ANOVA is known to be adversely affected by non-normality, heteroscedasticity, and unbalanced design.Type I error and power rates are substantially affected when these problems occur simultaneously.Continuously using ANOVA under the influence of these problems eventually will result in unreliable findings.Normality and homogeneity are two assumptions that need to be fulfilled when dealing with classical parametric test and not all data encompassed with
these assumptions.Thus, this study proposed a robust procedure that insensitive to these assumptions namely Parametric Bootstrap (PB) with a popular robust estimator,
MAD,.The p-value produced by modified PB was then compared
with the p-value of ANOVA and Kruskal-Wallis test.The finding showed that modified PB able to produce significant result in testing the equality of central tendency measure.
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