The phrase "across variables" is correct and usable in written English.
It can be used in contexts involving comparisons, analyses, or discussions that involve multiple variables in research, statistics, or data analysis.
Example: "The study aimed to identify trends across variables such as age, income, and education level."
Alternatives: "among variables" or "between variables".
The coefficient of variation confirms this, with no industry category achieving predominantly lower or higher variability across variables.
As expected, as it is very sensitive to the administration of opioids, the proportion of undertreatment falls substantially approaching 5%, with little variability across variables (type of centre and patient).
This produces rough standardized coefficients that allow comparisons across variables.
These were stable across variables of treatment, genotype, tissue and growth stage.
To achieve successful gene expression analyses for drought tolerance studies in rice, reference gene selection should be based on consistency in expression across variables.
Along the pine barrens but not the small block, there were two peaks of resolutions of correlation that appeared consistently across variables.
The portion of variation absorbed by the fixed part of the model differed markedly across variables, as showed by R2 statistics which ranged from 11.3%to78.3%3%.
Two examples from the pharmaceutical sector are discussed to illustrate the different ways to deal with uneven samples across batches and across variables in the same batch.
Neuropsychological scores beyond a standard deviation of ±3.0 were curtailed to values of +3.0 or −3.0 (depending on the direction), enabling a consistent range across variables as previously described (Naismith et al. 2002; Hermens et al. 2011).
The tPA (n = 78) and control (n = 156) groups were matched across variables, except for stroke severity, which was better in the control group; subsequent analyses controlled for this mismatch.
The amount of missing data for these variables was examined by demographic groups (gender, race/ethnicity, and free/reduced lunch status); and missingness was further examined across variables created from the NSRE and EMAS as these surveys were administered at different times.
