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First, stepwise multiple liner regression was employed as a descriptor selection procedure.
Binary logistic regression was employed as a model to predict AIEC pathotype according to the nucleotide present in a particular SNP position.
The stepwise regression was employed to select the optimum subset of the independent variables.
Linear regression was employed to determine if biodegradation rates were correlated to microbial growth.
Stepwise regression was employed to examine the factors associated with noise reduction.
Spatial autocorrelation regression was employed to identify the geographic determinants of the urban landscape changes.
The evaluation of the results requires the use of multivariate calibration; partial least squares regression was employed.
An integrated methodology consisting of hot spot analysis and Poisson regression was employed to map potential disease risk areas.
Logistic regression was employed to analyze data collected from a statewide survey of rural landowners in the fall of 2015.
Stepwise regression was employed to develop a regression equation that would correlate %HIA with molecular descriptors and k′.
Hierarchical multiple regression was employed to determine how well the independent variables predicted student perceived knowledge and student perceived competence.
More suggestions(15)
depletion was employed
regression was performed
reduction was employed
decay was employed
regression was preferred
loss was employed
degradation was employed
regression was demonstrated
regression was applied
regression was operated
regression was calculated
regression were employed
regression was described
regression was estimated
regression was conducted
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