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For this difference a p value of 0.06 was obtained by the parametric test.
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Although not all the criteria for normal distribution are met by this selection the parametric tests are robust enough to be used.
Non-parametric tests were applied whenever the data did not fit the assumptions made by the respective parametric tests in order to base the conclusions drawn on conservative estimates of significance.
This condition is often violated by the weighted parametric tests above.
The affect and perception survey responses were analyzed by the non-parametric test of Mann-Whitney U to check for significant difference between group responses.
Data were analyzed by the non-parametric test of Kruskal-Wallis ANOVA and a Mann-Whitney test.
Statistical tests of one way analysis of variance (ANOVA) followed by the non-parametric test of Kruskal Wallis were used to determine significant differences between different experimental groups and the controls by using GraphPad Instat 3 (GraphPad, San Diego, USA).
Accordingly, continuous variables were compared by either the parametric t test for unpaired samples or the non-parametric Mann-Whitney U test.
Cytofluorimetric results were statistically analyzed by using the parametric Kolmogorov Smirnov test using Cell Quest Software.
Frequencies of the categorical variables between pairs of subgroups were compared by the Chi square test (a parametric test) or by the "Fisher-Irwin exact test (a non-parametric test for small samples).
Adjustments were made for the most important predictors identified by the non-parametric tests (i.e., gender, headache diagnosis, HADS-total, PCS-12, and years with headache).
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