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This paper is an exploratory study of the relationship of these variables to safety.
The regression results in the next section will offer more precise estimates of the relationship of these variables to completion probabilities.
For this reason, it is worth exploring the relationship of these variables with the wage gap in a multivariate regression framework.
Note that the inclusion of endogenous covariates is not a serious problem, given that the relationship of these variables with turnover is not the focus of the analyses.
It can be argued that the relationship of these variables is not well understood (Devlin 2006) and that the interplay between the variables of professional growth are more complex than a linear model might suggest.
Even so, we cannot fully ascertain the causal relationship of these variables, because two of these variables (i.e., authentic leadership and psychological empowerment) are measured at the same time (Time 1).
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We then explore relationships of these variables to precipitation and extent of LGM glaciers to disentangle modern versus palaeo controls on the modern shape of the Alpine landscape.
Data were sufficient to describe the relationships of these variables with the productivity of bunchberry dogwood (Cornus canadensis), black crowberry (Empetrum nigrum), false toadflax (Geocaulon lividum), strawberryleaf raspberry (Rubus pedatus), lingonberry (Vaccinium vitis-idaea), and a combination of 24 other species.
To assess perifoveal capillary blood flow velocity (BFV), capillary occlusion, and retinal thickness at the central fovea in diabetic patients with or without clinically significant macular edema; to examine the relationships of these variables with visual acuity (VA); and to identify their contributions to visual outcome and diabetic macular edema.
As far as these socio-demographic variables are related to actual health, the relationships of these variables with the EQ-5D-3L items also provide information about the items' validity.
We investigated possible relationships of these variables with age, educational level, household income, family history of osteoporosis, menopause before age 45 years, fecundity (children per woman), lactose intolerance, caffeine consumption, low in calcium diet, and use of aluminum antiacids.
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