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Our second challenge was that, when comparing students' performance on two different tests, differences in test difficulty might systematically bias the results.
The power of the tests are heavily dependent on the parameter values, even though the between tests differences in power were consistent across the different parameters in this evaluation.
For low-stakes tests, differences in PD have been reported on a country level for the PISA assessments (Debeer et al. 2014; Hartig and Buchholz 2012; Jin and Wang 2014).
However, based on the results of our preliminary tests, differences in material temperature primarily affect the shape of the low-energy neutron spectrum but have small effects on the neutron density.
Differences in age, EDSS and disease duration between these groups defined by history of optic neuritis were assessed with Kruskal-Wallis tests, differences in gender with Pearson's Chi Square analysis.
Differences in means where evaluated using T tests, differences in medians were evaluated using the Mann–Whitney U test and difference in proportions were analyzed using the chi-square test.
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An unpaired Student's t-test was used to test differences in osteoblast differentiation, and significance was set at 0.05.
A one-way ANOVA was used to test differences in the changes for each outcome variable by BMI category.
Analysis of Similarity (ANOSIM) was used to test differences in community structure within the samples (1000 Monte Carlo permutations).
Bar plots of beta values (+/− SEM) of clusters resulting from whole brain RFX ANOVA testing differences in distraction versus engagement in anger or happy stories.
A one-way ANOVA was used to test differences in the changes for each outcome variable in non-exercisers and exercisers.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com