Analysis by stepwise multiple regression demonstrated independent correlations of duration of labour with parity (coefficient of determination R2 = 0.0489, R-adjusted = 0.039, P < 0.05) and with CR (P < 0.05).
Statistical analyses using SPSS version 12.0 (SPSS, Chicago, IL) consisted of simple correlation followed by stepwise multiple regression.
These retention times were modelled by stepwise multiple linear regressions.
By stepwise multiple regression analysis, Δvisceral adipose tissue area was the major determinant for ΔHOMA index.
The established QSRR models were built by stepwise multiple linear regression (MLR) and partial least squares regression (PLS).
The correlations among significant soft tissue changes and independent variables comprising treatment modality, age, sex, pretreatment skeletal, dental and soft tissue morphology were evaluated by stepwise multiple regression analysis at a 0.05 significance level.
Variable selection and model development were carried out by stepwise multiple linear regression methodology.
Influence of remnant forests and topographical variables on the spatial variability of rainfall were determined by stepwise multiple regression method.
For evaluation of the factors influencing soft tissue profile changes, correlations among significant soft tissue changes and independent variables comprising age, sex, treatment modality, pretreatment skeletal, dental and soft tissue morphology (Fig. 3) were evaluated by stepwise multiple regression analysis at a 0.05 significance level.
The ratio of DER over actual administered dosage becomes practically constant when we correct DER using the independent variables, as indicated, by stepwise multiple regression analysis.
