Sentence examples for indicators to predicting from inspiring English sources
Although the link between structural attributes and care processes has been shown to be inconsistent, the literature reviewed contains a number of examples illustrating the potential application of structural indicators to predicting the performance of nursing processes.
The abilities of disease activity indicators to predict one-year radiographic progression were evaluated by positive and negative predictive values (PPV and NPV, respectively).
It was founded by Geoffrey H. Moore, an economist who helped originate the practice of using leading indicators to predict business cycles.
Traditional technical analysis relies on some statistics (i.e. technical indicators) to predict turning point of the trend.
Finally, we show that the hydropathy index and charge of pore amino acids are important indicators to predict how pore mutations will affect growth on 1,2-propanediol, likely by controlling diffusion of one or more metabolites.
Of the four constructs of information quality, perceived usefulness and attitudes were found to be significant indicators to predict the customers' purchase behavior using the lodging Web sites.
True calibration of soil quality requires more than merely comparing values across management systems; (2) increase the power of soil quality indicators to predict response to disturbance.
The selected papers exemplify the use of observational and experimental approaches to identify mechanisms of ecological change in forests, and the use of indicators to predict current and future patterns of biodiversity.
Bhattacharyya [34] compiled several analytical studies that use different indicators to predict the performance of a system in various aspects.
We then used the coefficients of only the student body background indicators to predict earnings based only on student quality before entering college.
Regarding general problems with census data, King (2001) extensively discusses the limitations of using socioeconomic indicators to predict a community's vulnerability to natural hazards.
