Interpretation of Logistic Regression Output
Hi All --
I am working on an analysis to try and determine whether employee tenure (months at the company) has an influence on whether or not the employee has visited an office location in the past 3 weeks.
I have a dataset that includes a categorical variable "VisitedOffice" which indicates a 1 if the employee has visited the office and 0 if they have not. I chose to use a Logistic Regression as that seems to make the most sense for my categorical dependent variable.
For my independent variable, I have put in "EmplyeeTenure" which is a scale value that represents the number of months the employee has been at the company.
My output is as below:
I recognize that this model isn't very predictive as the % correct is only 60% and the R-square is less than 2%.
Am I correct to interpret this as: A one month increase in tenure increases the likelihood of visiting an office by 1.2%. However, the model is not statistically significant, and indicates tenure does not appear to have an impact on whether or not an employee has visited an office.