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Significant parameters were selected using the backward selection technique, where factors not significant at 0.1 were drawn one by one out of the model.
The final model was selected by using the backward selection method in multivariable logistic regression.
After determining bivariate associations between variables (using Spearman correlations for continuous variables and two-tailed t-tests for dichotomous variables), risk factors will be selected for entry into logistic regression models using the backward selection method, the outcome variables being the end-points outlined above.
Selection of all significant variables was conducted using the backward selection model.
In contrast, total telomere length was not associated with FMD value on multivariate regression analysis using the backward selection procedure.
After that, multiple linear regression analysis using the backward selection method was performed to estimate the effects of measures of obesity on cardiac structure alteration.
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Multivariate models used the backward selection technique and an alpha of 0.50 [18].
To identify the significant correlates of sleeping quality from the eight SF-36 domains of both age-specific and across age groups, logistic regression using the backward variable-selection method with entrance and removal levels of 0.05 and 0.10 were conducted separately for each age group for the complete sample.
# The variables were selected using the backward Wald stepwise selection method.
To determine factors affecting total IgE levels, we performed a logistic regression analysis using the backward stepwise method for variable selection based on the likelihood ratio.
Secondly, we used the backward feature selection (BFS) algorithm based on SVR to search for the feature combinations.
More suggestions(15)
using the same selection
using the best selection
using the backward cloud
using the backward stepwise
using the backward masking
using the backward method
using the quick selection
using the backward difference
using the backward procedure
using the backward substitution
using the backward observer
using the backward likelihood
using the random selection
using the backward flow
using the 'freehand selection
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