Sentence examples for by applying multiple regression from inspiring English sources
By applying multiple regression analysis on the experimental data, a second-order polynomial equation was obtained in terms of process variables as per Eq. 3.
By applying multiple regression analysis on the actual data, models for each of the three responses were expressed by the following quadratic polynomial model as shown in Eqs.
By applying multiple regression analysis on the experimental data, the experimental results of the CCD design were fitted with a second-order polynomial equation for chitinase activity.
By applying multiple regression analysis to the test results, a second-order polynomial equation (5) was obtained in order to represent lipid content as a function of glucose concentration, ammonium tartrate concentration, and harvesting time.
Figure 7B shows that by applying multiple regression, we reveal that in the selective populations of neurons, there is a variation across time in factors that influence their firing rates.
By applying multiple regression analysis to hippocampal LFPs recorded from rats performing a modified T-maze task (an eight-shaped maze), Montgomery et al. (2009) have previously shown that maze region (e.g., decision arm vs. return arm) better accounts for variations in theta power than locomotion speed.
Applying multiple regression analysis, the results were fitted into a second-order polynomial (2).
To estimate the amount of genetic variance explained by the SNPs, we applied multiple regression models using gene-centered forward selection.
Finally, risk factors were assessed by univariate Cox regression analysis, and variables that were statistically significant (P < 0.05) were included in multivariate analysis by applying multiple Cox regression analysis based on forward elimination of data [ 11].
By applying multiple linear regression analyses to investigate relative association strengths of olfactory target measures with several symptom domains, odor interpretation, but not naming, was found to be influenced by the severity of positive symptoms.
Risk factors for hospital mortality were analyzed by univariate analysis, and the variables statistically significant (p <0.05) in the univariate analysis were included in the multivariate analysis by applying multiple logistic regression based on backward elimination of data.
