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Structural and biochemical analyses have shown the significance of a variable C-terminal tail in regulating acetyltransferase activity.
Furthermore, it allows researchers to go beyond merely determining the statistical significance of a variable.
The LRT test was used to test the significance of a variable (Table 3).
In multivariate models, the prognostic significance of a variable depends on the prognostic significance of MVD values using Mab to CD105 and vice versa.
Even though the functional significance of a variable glutamine repeat length in the SK3 channel protein has remained unclear, it has been investigated in the context of certain pathologies in humans.
These new values are then used in a regression analysis to determine the β coefficient, which allows us to compare the relative significance of a variable in contributing to the model by measuring all variables on an equivalent scale.
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The significance of adding a variable or an interaction term into the model was tested with Pearson's chi-square test (P < 0.05).
However, one difficulty with this type of analysis is the multi-colinearity between predictors, as the level of significance of a given variable in a model may be affected by another correlated variable in such a way as to confuse epidemiological interpretation.
To determine the significance of an added variable (i.e., whether the coefficient for the added variable was nonzero), we performed a log-likelihood ratio test.
Then the significance of an indicator variable is determined by a Wald statistic (the ratio of the corresponding coefficient in the fitted logistic model and its standard error) and indicates whether or not the gene is differentially expressed.
Statistical significance in the row of a variable name indicates overall significance of all categories combined including missing category.
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CEO of Professional Science Editing for Scientists @ prosciediting.com