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All of the shortlisted variables were included in an initial full model, and variables that did not explain a sufficient amount of variability in the data were removed from the model one at a time.
where j is the ID of the least probable CA model and variables with subscript + are the updated variables.
Therefore, one needs to select cautiously the model and variables based on the research goal, the statistical foundation, and the theoretical support.
Following this, we introduce the analytical strategy employed, which is propensity score matching, and move on to describe the data, model and variables used.
The main objective of this study is thus to contribute to the debate over nuclear energy and the environment with an enhanced model and variables.
In logistic regression analysis, all variables for which the P value was less than 0.15 on the univariate analysis were included in the model, and variables with lower significance (higher P value) were sequentially removed from the model.
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The model and variable selection is key to multivariable analysis.
Model and variable selection were based on descriptive results and univariable regression for the outcome of fatality.
Although our model is restricted to input-oriented model and constant return to scale, one can easily generalize it to output-oriented model and variable return to scale.
If a published biomass equation is the result of an intensive model and variable screening process, we must expect optimism in published statistics and model-bias [68].
Nevertheless, the discrepancy between self-perceived familiarity with the model and variable interpretations of the model features is striking.
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