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The random training set split tool (set test size for the data: 0.2) was then used to split the training set and test set.
Entries in the table show the power (for μ* > 0) and the test size (for μ*=0) for the likelihood ratio (LRT) and Wald tests from logistic regression and the Delong et al. test comparing the AUCs.
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Do this for μ*=0 to estimate the test size, and for larger values of μ* to assess a range of powers.
The dimensions of tensile test specimen size for ASTM used were 3 mm × 12.5 mm × 60 mm.
The dimension of flexural test specimen size for ASTM D790 (ASTM 2013b) used was 3 mm × 40 mm × 140 mm.
Figure 4a also shows a moderate effect of test set size for the two overoptimistic cross-validation variants (stronger underestimation for smaller training set sizes).
The dimension of Izod impact testing specimen size for ASTM D256 (ASTM 2013c) used was 3 mm × 10 mm × 55 mm.
We applied a relatively equal percentage of the aRNA yield from the two test samples sizes for the respective labeling reactions.
Differences are tested using Wilcoxon tests for size and MANOVA for shape and MANCOVA for allometry.
The test has nominal size for the null hypothesis even if the model m is mis-specified and if the covariates are measured with error.
Similarly, when the same outcome had been measured with more than one test (e.g. different attention tests), we calculated the effect size for each test and used their average.
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