In health research, especially studies conducted in practice settings, data commonly have a hierarchical nature, with variable measures – such as cholesterol measurements – clustered within different levels of the hierarchy [ 15].
To establish construct validity [ 75], PLS examines convergent and discriminant validity of the scale estimating how well a variable measures what it is intended to measure [ 45] or how well the measurement items relate to the constructs [ 80].
A second variable measures the treatment intensity from the fraction of affected employees.
This place variable measures the prevalence of specific crimes at the stations.
This variable measures intra-ASEAN investment flows, and the expected sign is positive.
This variable measures the extent of integration between Japan and the SAFTA countries via FDI.
This variable measures the temporal clustering of initial crimes within micro-time hot spot.
The dependent variable measures whether an immigrant group protested in at least one instance.
This variable measures the relative intensity of the initial micro-time hot spot.
This variable measures the ease of access and the potential level of activity around the stations.
Finally, the fifth variable measures whether the applicant is engaged in sport activities or not.
