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Abstract:
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In clinical studies, it is not uncommon that data are challenging to analyze because they are heavily skewed. Therefore, the common methods of normality assumption in hypotheses testing are not met. This research work is to present the rationale behind statistical applications and review useful tools for skewed data analyses including, but not limited to, slope analysis by random coefficient models of parametric approach and shifting analysis among categories of distribution-free approach. In addition, examples in renal function parameters from clinical study are demonstrated.
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