The phrase "active variable" is correct and usable in written English.
It can be used in contexts such as programming, statistics, or research to refer to a variable that is currently being manipulated or is influencing the outcome of a process.
Example: "In this experiment, the active variable is the temperature, which we will adjust to observe its effect on the reaction rate."
Alternatives: "controlling variable" or "manipulated variable".
The physically active variable was dichotomized as 1 (sufficient; ≥150 min physical activity per week) or 0 (insufficient; <150 min/week) and was derived by calculating the number of minutes of physical activity per day (hours × 60 + minutes) and then multiplying by 7 to obtain a weekly value.
The active variable stiffness (AVS) systems may be effective for response control of building structures subjected to earthquake excitations.
It has been demonstrated that active variable stiffness (AVS) systems may be effective for response control of building structures subjected to earthquake excitations.
Because why was it necessary to conduct a study to see if this is an active variable within men's decision-making towards deciding whether he finds someone attractive or not?
Normal-phase separation of technical grade nonylphenol (t-NP, about 90% 4-nonylphenol), 4-nonylphenol mono-ethoxylate (4-NP1EO) and 4-nonylphenol di-ethoxylate (4-NP2EO) wassessedsed, with the inclusion of column temperature as an active variable.
The active subspace identifies one-dimensional structure in the map from simulation inputs to quantity of interest that allows us to reparameterize the operating conditions; instead of seven physical parameters, we can use a single derived active variable.
Ambient motion and gravity are the active variables here.
In this paper, we propose a method for screening out the important factors from a large set of potentially active variables, based on an information theoretical approach.
Supersaturated designs are a large class of factorial designs which can be used for screening out the important factors from a large set of potentially active variables.
The Random Forest (RF) module of R monotonously increases the number of active variables until the out-of-bag (OOB) error no longer decreases.
And so, two types of variables were distinguished: active variables which contribute to create factorial axes, and illustrative variables which permit to improve the analysis by calculating the Pearson's chi-square (χ2).
