In addition to fatherhood, on both unadjusted and adjusted linear regression, AGD was significantly correlated with sperm density and total motile sperm count.
Multivariable-adjusted linear regression (SAS Enterprise Guide 4.3) was used to examine the association between PCA factors with measures of physical function.
The fuzzy linear regression (FLR) was used and compared with the multiple-linear regression (MLR) analysis.
After the variable selection, multiple linear regression (MLR) was utilized to construct linear QSRR models.
The descriptors were further employed in the development of QSAR regression model using PLS, multiple linear regression (MLR), and SVM.
The parameters of the model, for each response variable, were estimated by multiple linear regression (MLR).
Current approach uses multiple linear regression (MLR) technique for time and cost estimations.
2D-QSAR studies for ironporphyrin catalysts were performed by using multiple linear regression (MLR) analysis.
Partial least square (PLS) and multiple linear regression (MLR) employing pre-processing techniques were carried out.
The established QSRR models were built by stepwise multiple linear regression (MLR) and partial least squares regression (PLS).
The dominance of complex seasonality over typical calendar season was established through analysis and using Multiple Linear Regression (MLR).
