The phrase "observable variables" is correct and can be used in written English.
It refers to any measurable or visible factors that can be observed and measured. Example: In scientific experiments, researchers often analyze the relationship between observable variables, such as temperature and reaction time, to draw conclusions about cause and effect.
In the formulation described in the section above, model residuals are regarded as independent, and recursive effects are used to model (interpret) patterns of co-variability between observable variables.
With both exploratory factor analysis [ 23] and confirmatory factor analysis [ 24] we are interested in explaining the variability in the observable variables (e.g. symptoms, questionnaire data) by modelling common latent factors (e.g. depression severity).
Using this kind of analysis, one tries to define an underlying factor that cannot be observed or measured directly from other observable variables.
Additionally the full structure of the Jacobian, through its singular value decomposition, is exploited in order to state classification rules for the process variables with regards to redundancy and observability as well as to obtain estimates of observable variables.
Phenomenological equations are always written in terms of directly observable variables.
Studying migrants' last US trip helps to understand the selection among migrants on observable variables.
γ captures the effect of time-changing observable variables on the outcome.
It is an iterative computation method of maximum likelihood estimates of missing data from observable variables.
The model allows the measure of LOC to depend on observable variables.
They conclude that long-run changes in relative wages can be mainly explained by observable variables.
Ability and experience cannot be captured by the observable variables in our regression.
