Preferring Box-Cox transformation, instead of log transformation to convert skewed distribution of outcomes to normal in medical research
نویسندگان
چکیده
BackgroundWhile dealing with skewed outcome, researchers often use log-transformation to convert the data into normal and apply commonly used statistical tests like t-test, linear regression, etc. However, log-transformed will not be at all times. In such situations, Box-Cox transformation (BCT) can transform normal. problem arises when researcher wanted predict outcome in original scale. Therefore aim of this paper is demonstrated BCT for a scale, using regression method.Materials methodThe Cost Pyelonephritis Type-2 Diabetes (COPID) study was demonstrate back method. This conducted among patients admitted general medical wards tertiary care hospital from south India. The applied total cost it multiple method predicted values were transformed scale.ResultsThe estimated lambda −0.36. After BCT, approximately (p-value = 0.621). residual plots suggested that error follows variance constant. median (IQR) observed 57694(42405, 98621) whereas 58317(44270, 95375).ConclusionWhen skewed, appropriate scenarios. ensure distribution after also we scale given covariates.
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ژورنال
عنوان ژورنال: Clinical Epidemiology and Global Health
سال: 2022
ISSN: ['2213-3984', '2452-0918']
DOI: https://doi.org/10.1016/j.cegh.2022.101043