stepwise

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stepwise

incremental; additional information is added at each step.

stepwise multiple regression
used when a large number of possible explanatory variables are available and there is difficulty interpreting the partial regression coefficients. s. prospective trial see prospective trial.
References in periodicals archive ?
The results from stepwise multiple regression analysis, controlling for depression, demonstrated that of nine selected demographic and clinical variables, the best predictor of fatigue severity was activity restriction.
A stepwise multiple regression analysis was selected to determine the amount of variance added to [R.
A stepwise multiple regression, using age as a dependent variable and the best friend variables as predictors, entered closeness into the analysis.
Table 5 displays the results of the stepwise multiple regression (probability of F-to-enter [0.
Stepwise multiple regression analysis of log serum GH basal concentrations confirmed a significant influence of the GHR genotype on the relationship between GH and IGF-1 concentrations, even when additional variables with known effects on GH concentrations were considered (such as sex or age of patients).
Backward stepwise multiple regression analysis revealed that albumin and creatinine were related to F:T.
In this study after calculated the correlation coefficients between the research variables by using the Pearson's correlation coefficient, all variables that have a significant correlation with the dependent variable management of field capabilities, was entered into the Stepwise multiple regression equation.
Stepwise multiple regression is an exploratory technique, where one independent variable is added at a time and checked for significant improvement to predict the dependent variable.
Stepwise multiple regression analysis was also performed to find an association of SBP, DBP and mean arterial blood pressure (MBP) with demographic and body composition data which had p value <0.
In addition, a stepwise multiple regression was conducted for hypothesis six.
Stepwise multiple regression analysis was carried out to find which cluster of values best predicted each component of commitment.