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Based on the results of factor analysis, two separate stepwise regression analyses were conducted to investigate the relationship between students' perceptions of assessment tasks and classroom assessment environment.
Second, variables that were correlated (p values <.2) with the dependent factor (ASD/PTSD symptomatology) were included in multivariable stepwise regression analyses.
Independent parameters representing geometric features and speed at the preceding section were logically selected in stepwise regression analyses to develop the models.
Forward stepwise regression analyses are conducted to determine statistically significant variables from 34 candidate predictor variables and to propose the empirical equations of the modelling parameters.
Linear and stepwise regression analyses showed baseline seizure frequency and lifetime seizure count to be significant (P < 0.05) predictors of the stabilized dosage.
The stepwise regression analyses showed that oxalate-extractable iron (Feo) was likely one of the most active iron sources for soil Fe(III) reduction.
Regression models generated using stepwise regression analyses were used to plot response surface curves, to study the tempering behaviour of products.
Next, we investigated the predictive ability of section III personality traits in relation to section II personality disorders through correlations and stepwise regression analyses.
After performing stepwise regression analyses, a series of response surface models of the dependent variables at each time step were constructed and validated using appropriate goodness-of-fit measures.
We used a test criterion value of 1.0 in the stepwise regression analyses.
Secondly, stepwise regression analyses were used to determine independent predictors of endurance time during CET.
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