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Besides assessing the performance of different models, we tested the differences of the best model parameters among the three forest soils using analysis of variance (ANOVA).
Furthermore, we tested the differences in SOM decomposition rates between grasslands and shrub vegetation.
Finally, we tested the differences among groups with respect to each of the paths included in the model.
*P < 0.05: When we tested the differences of main arterial pressure between the time points considered, a statistically significant difference was found (P < 0.05).
To further validate the above results, the present study randomly selected the RNAs from 42 male gout patients and 46 healthy males and tested the differences in the mRNA levels of the candidate genes.
Finally, by using t-tests, we tested the differences between the average regulated prices and the prices determined by firms in the tenders before the price regulation was implemented (Table 12).
To understand the scale dependence of regression algorithms for predicting LST, we developed individual models (local models) at four spatial resolutions (480 m, 240 m, 120 m and 60 m) and tested the differences between these using RMSE derived from cross-validated samples.
To validate cluster-specific associations, we tested the differences in HRV and β-AR genotypes in estimated clusters based on first- and second-half ECG data.
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We also tested the difference in mean values with a paired t-test.
To test the differences among different treatments, variance analysis was performed using SPSS 20.0 statistical software.
The Chi-Test was used to test the differences in prevalences.
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