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Interactions identified during the modeling process were evaluated in subsequent models; no interaction remained in the final model.
However, such influence lost statistical significance when adding key variables in subsequent models.
Although many improvements were made in subsequent models, this model lays the foundation for the rest of the RRAM models by accurately taking into consideration and explaining the non-linear dopant drift effects [3, 46].
Thus, those variables were omitted in subsequent models.
Note also that when exploring the first model, I provide definitions of most parameters and analytical methods used in subsequent models.
A product term representing the interactions between suicidal ideation and NSSI was also included in subsequent models to test for differences in the association between NSSI and self-reported suicide attempts among youths with and without suicidal ideation.
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We conducted bivariate analyses for all remaining explanatory variables, and only those with a p value of <0.25 from chi-square testing were considered in subsequent model building.
The experimental design controls the structure of the population under consideration and is therefore a critical component to account for in subsequent modeling and testing.
Significant predictors (p <.05) were included in subsequent model building.
The measured expression ratio distribution for technical noise (SD = 0.11) was used in subsequent model computations.
Coupled with biological variability, it would be additionally challenging to be clear about model limitations in subsequent model usage.
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