![]() ![]() Keywords: Back-transformation Box-Cox transformation Homoscedasticity Logarithmic Normality Power Retransformation Skewed distribution Transformation.Īccording to the characteristics of data distribution, various transformation methods can be used to achieve satisfaction for the normality test ( Table 1). Back-transformation and other important considerations are also described herein. This article introduces general concepts about variable transformation, mainly focused on logarithmic transformation. Back-transformation is crucial for the interpretation of the estimated results. Variable transformation usually changes the original characteristics and nature of units of variables. The purpose of variable transformation to enable parametric statistical analysis and its final goal is a perfect interpretation of the result with transformed variables. Variable transformation provides an opportunity to make data available for parametric statistical analysis without statistical errors. Data collected from the clinical situation or experiments often violate these assumptions. Several assumptions such as normality, linear relationship, and homoscedasticity are frequently required in parametric statistical analysis methods. ![]()
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