To obtain the main outcome variable for the sample size calculation, the correlation coefficients were calculated between functional performance measures and variables of postural sway as obtained by modified sensory organization test on force platform.
Compared with a previous profile score that was based on the log-odds likelihood calculation, the correlation between predicted and experimental ΔΔG of single-site mutations is increased in this approach from 0.33 to 0.68.
When the non-painful stimuli were excluded from this calculation, the correlation remained basically unchanged (r = 0.797) - indicating that the two stimulus dimensions have similar correlation for both painful and non-painful stimuli.
Pearson or Spearman methods were used to calculation the correlation reported (Specified in the Results section).
When feed intake on the day before testing was included in the calculation, the correlation (r=−0.19) was weaker (Robinson et al., 2011).
The PROC PRINCOMP statement of the SAS system 9.3 was employed for the PCA calculations using the correlation matrix of the data.
Calculations of the correlation coefficient (r) of independent variables were assessed using Spearman correlation analysis.
Conversely, in the pairwise data sets with lower correlation coefficients (5A/5AsRNA, 5A/7i and 5A/9i), the ranked correlation calculations increased the correlation values by 0.021 0.098.
We also did calculations of the correlation between the normal or cancer cell viability and the activities.
For comparison, we also used one spot per block for calculations, where the correlation coefficients were 0.83 to 0.95.
