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Categorical and continuous variables were examined using standard univariate tests for comparison.
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Statistical analyses were performed using standard univariate and multivariate tests.
Univariate comparisons of patient characteristics, clinical problems, use of services and care provided will be undertaken using standard statistical tests (χ test for categorical variables and t tests or non-parametric equivalents for continuous variables).
Univariate analysis was carried out using standard processing steps in SPM5.
Univariate relative risk (RR) and 95% Confidence Intervals (CI) were calculated using standard cohort analysis [ 7].
Clinical correlates of EO were analysed using univariate tests and multivariate logistic regression models.
Univariate analyses used standard statistical methods, such as the χ test for comparison of proportions and the Kaplan Meier estimator and the log-rank test for the estimation and comparison of survival curves.
ANOVA was used thereafter for univariate tests between the independent variables and the items in the RIPLS, and mean and standard deviations were also calculated.
It is worth mentioning that univariate time series (STU) clustering algorithms use standard approaches using point-prototype grouping models.
A standard univariate t-test was applied using SPM5 to every voxel in the image in order to create a map from which statistical inference was drawn.
Survival comparisons were performed using univariate log-rank tests.
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