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A square root transformation corrected a significant positive skew on TCIP mean choice latency for immediate reinforcers.
This transformation corrected for the translocation of the two color images on the camera, as well as differences in the rotation and magnification in the two channels.
Results were calculated from the standard curve using a log-logit transformation, corrected for recovery and expressed as nmol testosterone per liter sample.
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This transformation corrects for the underestimation of the H/L ratio because of the metabolic labeling of proline and glutamate.
These analyses were based on recognition of a specific asymmetry of the BG measurement scale and on a nonlinear transformation correcting this asymmetry (15, 16).
Square root transformations corrected outlying data (z > 3) and heterogeneity of variance on the LEIDS-R total and subscales.
This transformation effectively corrected for any systematic error in the data introduced by 3' signal bias and significantly improved the quality of the data (see Supplementary Information S1).
In brief, data transformation was corrected for low signal, with intensity values <10 set to 10.
d significance level (Pc) calculated by the method of Fisher's transformation and corrected by Bonferroni.
In brief, data transformation was corrected for a low signal, with values recorded at <0.01 increased to the minimum (0.01).
Finally, the Box Cox procedure (Box and Cox 1964) was conducted on BLUPs of each trait to find the optimal transformation that corrected for unequal error variances and non-normality of error terms.
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CEO of Professional Science Editing for Scientists @ prosciediting.com