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The results were analyzed using analyses of variance (ANOVA) and the signal-to-noise (S/N) ratios by design-expert software for the optimal parameters, and a regression model was established.
Data were analyzed using analyses of variance.
Research questions were analyzed using analyses of variance and bivariate correlations.
Group mean differences in cell counts were analyzed using analyses of variance (ANOVA) with Tukey or Tukey-Kramer post hoc tests to examine pairwise differences.
Intervention effects were analyzed using analyses of co-variance (ANCOVA).
Numbers of action and evaluation errors were analyzed using analyses of variance (ANOVAs) with diagnostic group (patients vs. controls) as a between-subjects factor and trials (1 5 vs. 6 10) as the within-subjects factor.
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When appropriate, for example for the weekly pain ratings scales, scores will be analyzed using repeated analyses of variance to analyze and separate the effects of treatments and time and test the interaction between the two, as well [ 33].
The data were analyzed in JMP® (SAS institute) software using analyses of variance method.
The influence of interstimulus interval on each peak of the CAEPs was analyzed using Friedman nonparametric analyses of variance.
Date is presented as means ± SEM. Results of experiments were analyzed using One Way Analyses of Variances (ANOVA) with post hoc comparison via Bonferroni corrections.
Data were analyzed using regression analyses to evaluate relationships of the ƬE method for determining Pplt, Crs, and Rtot with the EIP method for determining Pplt, Crs, and Rtot, using analysis of variance (ANOVA, Fisherr's exact test, and Bland and Altman analyses [ 13].
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