I'm new to statistics and coding so apologize if this is a dumb question but here it goes:
I'm running a logistic regression model with a binary dependent variable and when I use a continuous variable as an independent variable (min 0, max 2,330), I get an OR of 1. When I categorize this continuous variable into 2 categories and run the regression model again using this new binary variable as independent variable, I get an OR of 22, p<0.001.
What is the most appropriate way to run it, using a binary or continuous variable? and why could it be that there is such a big difference?
Thanks!
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