Sentence examples for between each response variable from inspiring English sources

Where simple monotonic relationships between each response variable and pH were indicated, the significance of the relationship was tested by correlation analysis (either Pearson's or Spearman's) due to the well known insensitivity of ANOVA to monotonic gradients in responses [44] [46].

These coefficients are called the PLS scores, and these scores are defined as the associations between each response variable (mRNA) and the miRNA covariate for a specific i and j.

Partial least squares linear regression (PLSLR) analyses were performed to examine the relationships between each response variable, CH and CRF, and the predictor variables age, corneal curvature (CC), axial length (AL), CCT and IOP.

The associations between the covariates and each response variable were estimated by the chi-square test (categorical variables) and by the t test for means (continuous variables) using a significance level of p < 0.05.

Fractional polynomial regression was then used to identify the best fit transformation of gestational age to account for any non-linearity in the relationship between gestational duration and each response variable [ 19].

In a second step, we calculated the difference in responses/min for each response variable between the two speaker locations for each playback session and each response variable.

Due to the presence of variable degrees of asymmetry, the Wilcoxon test was used to compare the median of each response variables between study groups moments 0 and 1.

In the context of our additive models, the partial residual plots help us assess the relationship between the response variable and each smooth term, given that the other smooth terms are in the model.

We associated a residual density to each individual by considering the normalized sum of the model residuals (each measurement residual being the difference between the response variable and the fixed effects prediction of the model) for each individual.

Such a relationship between the response variable and explanatory variables is called a profile.

Regression modeling is used to establish relationships between a response variable and a set of spatial predictors.