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However, only one year of registration implies a restricted amount of these data so it was not possible to include soil cultivation in the multivariate statistical testing.
For univariate and multivariate statistical testing the following methods were used: Mann–Whitney test, Chi squared test, Spearman rank correlation, binary logistic regression, Logrank test and Cox regression.
The CoaguChek XS showed a slight difference in two types of clinical event in multivariate statistical testing; however, this is deemed not to be clinically relevant and more likely due to the multiple tests performed in the large population analyzed.
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Macrofaunal data were analysed through multivariate statistical tests, and for the orientation distributions the circular statistics were calculated and multivariate analyses for angular data were performed.
Multivariate statistical tests and contribution plots are also shown graphically.
Multivariate statistical tests such as clustering, principal component analysis, and multidimensional scaling were performed with Acuity 3.1 (Axon Instruments).
We employed bivariate and multivariate statistical tests.
CTES was shown to be significantly consistent within itself with P<0.05 using the Hotelling multivariate statistical test.
Univariate and multivariate statistical tests are used to assess any differences between groups in terms of efficacy and safety parameters.
In addition, generally accepted assumptions for multivariate statistical tests suggest that a multivariate model should have approximately 10 cases per parameter.
Ironically, the development of complex statistical techniques that allow for multivariate statistical tests without much knowledge of underlying mathematical principles has blunted our ability to draw on theory.
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