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From the results of multivariate tests in the next section, we show that the different sample periods cause this inconsistency.
Moreover, the use of multivariate tests in place of univariate tests does not solve the dilemma, because multivariate tests present their own shortfalls, including interpretation problems (if there is a difference between experimental groups, multivariate tests do not tell us which variable might differ as a result of treatment, and univariate testing may still be needed).
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Multivariate analysis was performed with a multivariate cox proportional hazard analysis in 18 and some other multivariate test in 7 reports.
F-values from multivariate tests are presented in the text, while P values from post-hoc t-tests are displayed in the figures and tables.
Multivariate tests showed differences in health and aging parameters between males and females, and further, differences in male fish between ages and between sites.
Rare variants can also be simultaneously analyzed with common variants in a multivariate test, as in the Combined Multivariate and Collapsing (CMC) method [11].
In multivariate analysis with the clinicopathological parameters (Table 2), the combined TGF- β1 level remained statistically significant in multivariate tests.
Only the candidates with adjusted P-values of ⩽0.05 in multivariate tests were selected for further analyses.
These data were used as explanatory variables in multivariate tests to reveal the most important factors influencing the Fusarium infestation and the mycotoxin contamination of the cereals.
The collected data were analyzed by SPSS software, Chi-square tests, independent T-test and the repeated measurement multivariate tests for measuring life quality in three different time periods.
The collected data were analyzed using SPSS software, Chi-square tests, independent T-test and the repeated measurement multivariate tests for assessing life quality in three different time periods.
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