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When comparing means of continuous variables between two groups using a t test, Cohen's d is a useful effect size measure that describes the difference between the means normalized to the pooled standard deviation (SD) of the two groups (see Table 1; Cohen, 1988).
This common course of analysis is to compare small-world characteristics between two groups using classical inferential statistics.
The extended gene transcript set was imported and normalized using the RMA (Robust Multiarray Analysis) algorithm, then compared between two groups using a one-way ANOVA.
Demographics data were compared between two groups using by a Chi-square test.
Data were analyzed within one group and between two groups using paired t-test.
Student's t-test was used to compare the mean differences between two groups using Statistica-6.0 software package.
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Comparisons between two groups used two-tailed Student's unpaired t-tests for parametric data or, in the case of basal extracellular GABA levels, Mann Whitney U-tests, based on the outcome of Shapiro Wilk normality tests.
Categorical variables were compared between three groups using χ or Fisher's exact tests when appropriate.
p < 0.0001 that there is a difference between the two groups using a two-tailed unpaired t-test.
Previous histomorphometry of the same material failed to detect a structural distinction between the two groups using established variables.
Continuous variables were compared between the two groups using Student's heteroschedastic two-tail t test.
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