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Higher education today faces challenges that would benefit from new approaches and calculated risk-taking.
Responsiveness was examined first using distribution-based approaches and calculated as Cohen's d, total score change, percent change and the standardized reponse mean across time periods.
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The value of Kf for the beam and CT specimens based on the author's approach and calculated by the well-known equations of Neuber and Peterson are compared.
[ 31, 32] We also used a distribution-based approach and calculated a standardised response mean (SRM).
We, therefore, used a non-parametric permutation approach and calculated standard errors and p-values based on 10,000 permutations.
We used a resampling approach and calculated an S value for each simulation to test the null hypothesis that there is no periodic relationship between the peaks.
Consequently, to avoid shrinkage, we modified the publicly reported measure approach and calculated observed-to-expected risk ratios for each cohort instead of predicted-to-expected ratios.
However, we slightly changed their approach and calculated the average of the normalized fluorescence signal for each standard over the entire temperature interval instead of using single values at chosen temperature points.
To circumvent this, we chose an a priori approach and calculated a food pattern score based on the intake of 10 individual food groups previously associated with type 2 diabetes risk (1– 7, 9– 12) that we found to be significantly inversely associated with risk of type 2 diabetes in MESA.
Therefore, we consider it as a typical chip of direct gene-centric approach and calculate tagged SNPs in HapMap.
Gene cluster analysis was performed with the REEF (REgionally Enriched Features in genomes) program, which scans the genome using a sliding window approach, and calculates the statistical significance of each window using the hypergeometric distribution and the false discovery rate [ 22].
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