The phrase "observational variables" is correct and usable in written English
It is typically used in the context of research, statistics, or data analysis to refer to variables that are measured or observed in a study.
Example: "In our study, we focused on several observational variables, including age, gender, and income level."
Alternatives: "measured variables" or "observed variables"
In this example the observed correlation between schooling and earning could emerge because of effects of IQ on both observational variables and not a causal relationship between the observed variables.
To assess construct validity, a compliance task was utilized to determine whether children identified as high on anxiety/withdrawal, anger/aggression, or social competence with the parent version of the SCBE-30 (n=20 for each group) could be distinguished behaviorally on several observational variables.
In previous applications we assumed that all models θ have the same causal structure, i.e. considering multivariate random variables a t and o t, we assumed that the same variables a t are intervened for all θ and the same causal model is used to predict the consequences of these interventions on the observational variables o t.
The consistency of observational variables was calculated in Table 3.
This indicated that the observational variables were derived from the latent variables.
Firstly, it is cross-sectional design that precludes from drawing conclusions concerning the causal relationships among the observational variables.
A parameter estimate was calculated for each latent and observational variable, to determine statistical significance and evaluate convergent validity.
Additionally, while most human clinical probiotic trials are well-standardized using the same strains, uniform dosages, regimens of the probiotic treatments and similar host age, animal studies often lack standardization, have variable experimental designs, and non-uniform and sometime limited selection of experimental variables or observational parameters.
Times were significantly positively correlated with all four observational environmental variables.
Table 4 showed the association between walking path use and observational environmental variables, including lighting conditions, accessibility, cleanness, and organization of the activities.
After classifying the walking paths by location, positive associations between utilization index and observational environmental variables (including permanent and current ratings) were represented in both pair 1 and 2. Similar associations between a brisk walking prevalence and observational environmental variables were also found.
