I am working with a very large dataset that essentially covers the entire population of interest. I want to assess the linearity assumption between an independent variable and the log(odds) of the dependent variable in logistic regression.
There are different ways to check this assumption, with a typical method being to create a statistical term representing the interaction between each continuous independent variable and its natural logarithm. If any of these terms is statistically significant, the assumption is violated. Solutions include dummy coding the independent variable, or statistically transforming it into a different scale."
Given the dataset's size, how can I effectively check for linearity without overly relying on statistical significance, because with large datasets things tend to be really quickly significant? Or is it even necessary to check this assumption?