The nursing workload [measured using the Therapeutic Intervention Scoring System (TISS-76)] for all patients in the ICU during each day to average number of bedside nurses per shift on that day (workload/nurse) ratio, severity of illness (using Acute Physiology and Chronic Health Evaluation III) and hospital survival were analysed using net-benefit regression methodology and logistic regression.
The second part consists of the use of response surface methodology and multiple regression to develop an experimental design modeland to assess the individual and interactive effects of pH, power (Po), ZVI dose and H2O2.
Variables retained for the indicator were selected using the receiver operating characteristic curve methodology and polynomial regression.
An investigation was conducted to evaluate the effectiveness of a non-parametric statistical methodology of classification and regression tree (CART) [L.
RF are a non-linear statistical learning methodology for classification and regression.
The objectives were: (1) to locate QTL on the available linkage map, (2) to compare QTL obtained through the use of two different methodologies: linear regression and maximum likelihood, and (3) to determine the association between markers and traits.
We evaluated our methodology in different ranking and regression settings.
The study can also be interpreted as extending the correlation and regression methodology, often used to analyze variables defined at single moments, to the analysis of variables in a time continuous fashion.
The proposed methodology combines two techniques, FEA, and regression analysis to study the impact of various parameters and their interaction on the thinning of the sheet metal.
A subsetting experiment using a 30-year dataset of daily suspended sediment observations from the Mississippi River at Thebes, Illinois, was performed to determine optimal sampling frequency, model calibration period length, and regression model methodology, as well as to determine the effect of serial correlation of model residuals on load estimate precision.
