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One-way analysis of variance (ANOVA) was used to evaluate differences in parametric variables.
Between-group differences in parametric variables were determined by Student t test and in nonparametric variables by Mann-Whitney U test.
The independent samples t-test was used to compare differences in parametric data between PH patients and controls; Welch's correction was employed for unequal variances.
Data were statistically analyzed using SPSS computerized package by Fisher's exact test to compare differences in rates and Student t-test for differences in parametric data.
Analysis of variance was used to investigate differences in parametric variables, followed by Bonferroni's or Tukey's test to investigate differences in time in each group and between groups respectively (intraoperative cardiorespiratory data).
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The one-way analysis of variance (ANOVA) was used to evaluate difference in parametric variables.
While keeping that in mind, we find that difference-in-difference parametric models yielded somewhat higher point estimates with respect to their counterpart matching approach, particularly for men.
One-way analysis of variance (ANOVA) was used to examine differences in the parametric data among the three groups.
Group differences in continuous parametric variables (eg, age) were examined with the Student t test or 1-way ANOVA as appropriate.
Student's t test was used for age, number of awakenings, and sleep efficiency as parametric variables by child sex; Wilcoxon rank-sum test was used to test differences in non-parametric variables including sleep onset, sleep latency, WASO, awakening length and sleep duration by child sex.
The χ test, Mann-Whitney U test and Kruskal-Wallis test, were used to examine group differences in non-parametric variables.
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