Sentence examples for metric variables and from inspiring English sources

Difference between groups was tested with F-test for metric variables and Chi-square test for categorical variables.

The main baseline characteristics of the sample were analysed by calculating means and standard deviations for metric variables and percentages for nominal variables.

For variance analysis, we log-transformed data with uneven distribution and used linear regression analysis for metric variables and analysis of variance (ANOVA) for categorical variables.

Univariate associations between each dimension of the SF-36 scale and other variables of interest were assessed using ANOVA for metric variables and a χ test for categorical variables.

In a first step, all of those parameters were analysed with respect to their relation to TQ difference 2 using product-moment correlations for metric variables and a t-test for the discrete variable.

Descriptive statistics were conducted with independent and paired-sample t-test as well as one-way ANOVA (with Bonferroni's correction for multiple comparisons) for metric variables, and with χ2 and Fisher's Exact Test for categorical variables.

We also performed multiple regression analysis with stepwise forward selection of parameters for predicting mPAP at rest as metric variable and also for binary classification of PH (mPAP ≥25 mm Hg versus mPAP < 25 mm Hg).

Moreover, descriptive statistics over time are depicted in Table  2.> -wrap-foot>> Analyses of variance were used for the metric variables (GDS and Comorbidities), and chi-squared tests (with Cramer's V) for all other variables Source: AgeCoDe (Wave 3), own calculations Of the n = 1,882 participants in wave 3, 65.8 % were female (Table  1).

For metric variables median and inter quartile range, for categorical variables the absolute and relative frequency for each category are shown.

Partial correlations, adjusted for the participants' sex and age, evaluated the association between VG total score (considered as a dimensional-metric variable) and clinical measures.

Categorical data were expressed as absolute numbers (percent) and ordinal and metric variables as mean [±standard deviation (SD)] and as median [interquartile range (IQR)].