Sentence examples for performance measures data from inspiring English sources

It also highlights the potential challenges and barriers associated with performance evaluation of allied health practitioners, specifically in terms of selection of performance measures, data collection, and implementation of an effective performance evaluation strategy.

A consistent method of recording performance measures, data validation, and conditional formatting could be utilised in real settings to improve recording of the data that could provide the evidence-base for more tailored and appropriate services for a client group.

We hand-collect performance measure data from the Wind financial database.2 Our initial sample includes 1,147 firm-year observations with available performance measure data.

When performance measure data is missing from Wind, we hand-collect the data from firms' performance-vested stock option plans.

The tuning time and the access time are two performance measures in data broadcasting environments.

This difference among the results can be attributed to different performance measures, sample data, and different benchmarks used by these studies.

The parallelism and the randomness of the algorithm bring additional issues to the application of statistical methods for the evaluation of performance, such as the choice of performance measures, the data distribution of these measures, and the variability brought by parallel executions.

We are also seeing a renewed commitment to use performance measures and data to guide federal policy; this is an extremely welcome development that will pay dividends by ensuring that taxpayers funds are spent effectively and that those most in need are receiving assistance.

We calculated R values (explained variation in time to diagnosis of heart failure 27), D statistics 28 (a measure of discrimination where higher values indicate better discrimination) and the area under the receiver operating characteristic curve (ROC) statistic at 10 years, and combined the model performance measures across data sets using Rubin's rules.

Thus, there was a difference in the labelling methodology for different subsets of the local data, with algorithm training relying on data with a reference diagnosis based on visual assessment only, and reporting performance measured with data that had reference diagnosis based on clinical follow-up.

The analytical model is a generalization of the simulation outcomes under deterministic data, and the simulation model is used to probe and identify the inter-relationships and performance measures under stochastic data.