Log-transformation and its implications for data analysis.
University of Rochester · Stanford University
Abstract
SUMMARY: The log-transformation is widely used in biomedical and psychosocial research to deal with skewed data. This paper highlights serious problems in this classic approach for dealing with skewed data. Despite the common belief that the log transformation can decrease the variability of data and make data conform more closely to the normal distribution, this is usually not the case. Moreover, the results of standard statistical tests performed on log-transformed data are often not relevant for the original, non-transformed data.We demonstrate these problems by presenting examples that use simulated data. We conclude that if used at all, data transformations must be applied very cautiously. We recommend…
Citation impact
- FWCI
- 18.07
- Percentile
- 100%
- References
- 3
Authors
7Topics & keywords
- Transformation (genetics)
- Data transformation
- Gee
- Computer science
- Generalized estimating equation
- Data mining
- Statistics
- Data science