The data analysis in this study included two parts. We first evaluated the effect of addiction measurement. Both the dependent variable
(addiction) and criterion variables (the eleven experience factors) in this study were subjective self-report measurement. Therefore, the
measured addiction score needed to be examined in terms of the effect from an objective approach. To do so, we applied a correlation analysis
to see the relationship between subjective measurement (addiction) and objective behavior assessment (daily and weekly gaming habits)
to ensure validity of the addiction measurement in this study.
Second, we attempted to identify critical user experience factors that could be used to better predict game addiction. To do so, a linear
regression analysis was conducted to model the relationships between the eleven experience factors and addiction. Also, a multi-collinearity
analysis was conducted to detect the degree of collinearity present for the eleven predictors through calculating their variance inflation