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Study sample for continuous trait analysis For this part of the study we used participants from the ongoing New Hoorn Study, a population-based cohort study in the Netherlands, which examines potential determinants of glucose intolerance and related disorders [ 14, 15].
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When comparisons are possible, will utilize t tests for independent samples for continuous data, and χ tests for frequencies.
Analysis were done with t-test for independent samples for continuous variables and chi-squared test for categorical variables.
Clinical characteristics of the sample stratified by age were examined with chi-square tests for categorical variables and t-tests for independent samples for continuous variables.
These comparisons were made using a chi-squared test for categorical variables and Student's t-test for independent samples for continuous variables.
We first studied whether there were any significant baseline group differences using t test for independent samples for continuous variables and χ tests for categorical variables.
Differences between two independent samples for continuous data were analyzed using the Mann-Whitney U test (since the distributions of variables were different from normal).
Due to the exploratory character of the study dichotomous subgroups of survey participants were tested using the Mann-Whitney-U-Test for independent samples for continuous variables (i.e. subscales).
The new synthetic samples for continuous features are generated through the following steps [ 12]: Step 1: For each instance in the minority class, compute the distance between a feature vector of the instance and one of its k nearest neighbors.
49 51 52 Confidence intervals of the relative excess risk for interaction were estimated for statistical inferences by using the standard delta method described by Hosmer and Lemeshow 51 53 (for categorical arsenic exposure) and bootstrap method with 1000 bootstrap samples (for continuous exposure measure).
Within-discordant pair differences between the high and low-scoring twins on the PI-R ABBR were calculated using paired t-tests (t-tests for two related samples) for continuous data, Wilcoxon signed- rank tests for ordinal data and McNemar χ tests of matched pairs for nominal data.
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