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These retention times were modelled by stepwise multiple linear regressions.
Variable selection and model development were carried out by stepwise multiple linear regression methodology.
The established QSRR models were built by stepwise multiple linear regression (MLR) and partial least squares regression (PLS).
Multivariate determinants of log-transformed progenitor cell counts were identified by stepwise multiple linear regression analysis.
Predictors of Symptom Score improvement from baseline after 6 and 12 months were identified by stepwise multiple linear regression analysis (see Methods for details).
By stepwise multiple linear regression analysis, gender, age, location of spinal injury, neurological deficit (defined as ICD-9 codes recorded as 806.X or 952.X), surgical intervention and the six combined injuries were found to be factors that have a significant impact on the two types of medical utilization, LOS and direct medical cost.
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Predictors of functional change were calculated by a stepwise multiple linear regression model with baseline measurements entered as covariate factors.
The model was produced by using the stepwise multiple linear regression technique on a database that consists of 67 recently discovered 1,3,4-oxadiazole substituted naphthyridine derivatives.
By analysis using stepwise multiple linear regression, the factors associated with medical utilization were classified.
We used default cut-offs provided by SPSS in stepwise multiple linear regression (0.05 to enter in the model and 0.10 to be removed from the model) to choose the most influential independent variables.
The conventional 2D-QSAR models were developed by genetic function approximation (GFA) and stepwise multiple linear regression (MLR) with acceptable explanation of 94.9% and 95.5% and good predicted power of 91.7% and 91.7%, respectively.
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