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Statistical significance of the observations is often estimated using standard parametric tests, such as the t-test or ANOVA.
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Differences in mean costs will be analysed using standard parametric t-tests with the validity of results confirmed using bias-corrected, nonparametric bootstrapping (repeat re-sampling) [ 40].
Survivors and siblings were compared with regards to demographics, socioeconomic variables, healthcare utilization, and concerns regarding their future health using standard parametric and non-standard parametric tests.
Descriptive analysis will be performed, comparing the distribution of variables among cases and controls using standard parametric and non-parametric tests.
Confidence intervals were calculated using standard parametric techniques.
In others, a bacterial or viral infection was presumed on presentation but not identified in cultures or PCR (unknown) We used standard parametric and non-parametric testing to explore the relations between individual variables and the defined severe outcome (Table 3).
For each aim, we will use standard parametric and non-parametric techniques for observational data, including t tests, χ tests, Wilcoxon rank sum tests and generalised linear models.
This allows adjustment for age and sex and results in greater power than can be achieved using standard non-parametric tests.
Assuming the data prove to be normally distributed, standard parametric testing will be used to compare the mean QALYs in ICU survivors with the age and sex matched controls held in other databases.
To accommodate this data structure, we have used standard non-parametric tests throughout the analyses.
Results for CAM and non-CAM users were recorded as mean ± standard error and, where appropriate, analysed using standard non-parametric methods including Chi-squared test and Fisher Exact analysis.
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