Sentence examples for impacts of attributes from inspiring English sources

Flynn at al (2006) highlight the advantage of best-worst scaling over traditional discrete choice experiments as providing additional insights for health service researchers and allowing the impacts of attributes to be compared.

Since the ecological parameters and additional data inputs used in each of the simulations were kept constant, the observed differences in the estimates reflect only the effects of the spatial and temporal resolutions inherent to each of the RS observations, and the impacts of attributing cover changes to disturbance types with different impacts on carbon stocks.

The goal of this study was to evaluate the impact of attributes of the doctor-patient relationship on outcomes of patients who have undergone angioplasty.

Yet, such a development is critical for understanding the proper impact of attributes on resolution approaches, and to answer the needs of actual applications.

Certain issues in Health Services Research require analysts to compare the overall impact of attributes.

Consequently, the utility estimates represent a set of deviations that cannot be used directly to make statements about the overall impact of attributes [ 3].

This study is the first in health services research to separate the impact of attributes per se from their level scale values for various subgroups.

As the importance of different attributes cannot be compared directly using parameter estimates due to confounding with the underlying utility scales, the relative impact of attributes is usually examined by converting estimates to a common scale [ 79].

Whilst nearly all studies investigated the relative impact of attributes through willingness-to-pay and/or probability analyses, only five studies went on to combine impact measures with cost data to assess cost-effectiveness of policy options to varying degrees.

It may help policy-makers decide whether policies to improve levels of key attributes (for instance reduce the incidence of a given side effect of treatment) or those to increase/decrease the perceived impact of attributes themselves (for instance better education to improve patient understanding of a side effect) are the most desirable or feasible.

We found that dividing prediction capability for each attribute into those two (i.e. correct and faulty module prediction) facilitate understanding the impact of attribute values on the class and hence improve the overall prediction relative to previous studies and data mining algorithms.