While using a multiple linear regression model in this setup is conceptually appealing, use of visualizations may suggest the need for greater flexibility in the model.
To analyze factors associated with misdiagnosis a multivariate analysis was made using a multiple linear regression with diagnostic category as the dependent variable.
We compared managed (i.e., DWM) and free draining records using paired t-tests, and identified factors associated with DWM effectiveness using a multiple linear regression approach.
Average annual yields of the annual reference crops were modelled using a multiple linear regression approach which is based on yield levels from field experiments of 52 sites located in Lower Saxony [58].
Energy cost of chewing per minute was determined using a multiple linear regression model, with heat production per 10 min as the dependent variable and duration of activities per 10 min as independent variables.
A design of experiments (DOE) based on the Doehlert matrix was used to determine the optimum conditions of the method, and the influence of the variables was evaluated using a multiple linear regression (MLR) model.
In a next step, we evaluated the relationship between the parameters of the SOC depth model and co-variables including soil redistribution (inferred from 137Cs data) and topographical indices using a multiple linear regression model.
In this regard, 32 points among the 48 field observations were selected to determine unknown coefficients of models using a multiple linear regression, and the rest 16 points were designated for accuracy assessment the results.
Ea was calculated from a single dynamic thermogravimetric measurement using a multiple linear regression (nth order kinetics) method (i.e. the Wyden-Widmann's method [13]), by means of the following Arrhenius type equation: dα/dt = k0 e-Ea/RT (1-α n.
To estimate the contribution of the different variables on the wave number of the Neutral Red dye; the coefficients in equations (5) and (7) were estimated using a multiple linear regression analyses (where Δχ in equation 7 is used as the wave number of the dye in the different solvents), and the results are shown in Tables 3, 4 and 5.
In this study, quantitative structure-activity relationship (QSAR) models using various descriptor sets and training/test set selection methods were explored to predict the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by using a multiple linear regression (MLR) and a support vector machine (SVM) method.
