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The regression analysis used forward and backwards stepwise likelihood ratio (LR) methods.
A multivariate backward stepwise likelihood ratio regression analysis was performed, excluding parameters with high collinearity (Davg, D70, V50 and BED), verified by consideration of both clinical factors and correlation coefficients.
We employed multivariate logistic regression to predict LN involvement (method: backward stepwise, likelihood ratio).
All models: forward stepwise likelihood ratio.
-: indicated non-selected in the stepwise likelihood ratio model.
A forward stepwise (Likelihood Ratio) procedure was used for multivariable analysis.
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Binary logistic regression using backward stepwise likelihood-ratio for variable selection was carried out to determine the best predictors of group membership (PBL v non-PBL).
Variables in these analyses associated with survival time with a p-value < 0.05 were entered into a multivariate Cox regression model (Backward stepwise; Likelihood-ratio) [ 31].
Multivariate analysis of the independent prognostic factors for survival was performed using the backward stepwise (likelihood-ratio statistics based on the conditional parameter estimate) method of the Cox proportional hazard regression model with a 95% confidence interval (CI).
We performed stepwise backward likelihood ratio method and 0.05 of P-value was used as cut-point for likelihood ratio method.
We have already seen that the stepwise maximum likelihood estimation gave non-parametric LFs which agree reasonably with the assumed Schechter, or Saunders, function.
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