logarithmic transformation

logarithmic transformation

[′läg·ə‚rith·mik ‚tranz·fər′mā·shən]
(statistics)
The replacement of a variate y with a new variate z = log y or z = log (y + c), where c is a constant; this operation is often performed when the resulting distribution is normal, or if the resulting relationship with another variable is linear.
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For non-normally distributed data, logarithmic transformation was conducted for total CIRS scores.
Data that achieved a Gaussian distribution after logarithmic transformation are presented as geometric mean [95% confidence intervals (CIs)] (19).
Tumor markers were taken before and 3 weeks after the first cycle of CT, and it was found that the decline rate, using a logarithmic transformation of the tumoral markers, was a strong predictor of progression-free survival and overall survival in patients with poor-risk NSGCT.
The above review shows the general linear model or logarithm linear model by logarithmic transformation into linear equation is one of the most commonly used methods of building a highway traffic crash prediction model.
Multiple linear regression models for surface roughness can be obtained by applying a logarithmic transformation that converts non-linear form of eq.
Logarithmic transformation of miRNA-145 levels (Ln_miRNA-145) was used for statistical analysis due to the skewed data distribution.
Clearly, in all different specifications of the estimated equation, using alternative transformation of the unemployment series (logistic and logarithmic transformation), alternative disaggregation levels ([[sigma].sup.9.sub.t]) and [[sigma].sup.13.sub.t]), and different methods of estimation (OLS and GMM), we can observe a positive and significant relationship between unemployment rate and the measures of dispersion.
(2013) found that increased daily muscle soreness was significantly, negatively correlated (r = -0.53) with the natural logarithmic transformation of standard descriptor one of a Poincare plot (ln-SD1) in professional Australian football players throughout a training camp.
In order to demonstrate the calculation of a 95% confidence interval for the RR (the confidence interval shows the limit within which there is the certainty of the true treatment effect, estimates the magnitude of the association and informs the variability of the estimate through the lower and upper limits), it can be used the method described by the logarithmic transformation (Glantz, 2013).
Statistical analysis of the multivariate repeated SCC data was performed using a linear model with a Kronecker product structured error covariance matrix, after applying 10 base logarithmic transformation (SAS Inst.
Different transformations to the performance measures were applied a natrual logarithmic transformation to instability and cost measures was applied.
Logarithmic transformation maps input values to output values, compressing the higher values and expanding the values of dark pixels [9].