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!
Related Posts with Continuous vs binary independent variable in logistic regression
How do I drop dates => than 01.may 2013?When I write: drop if=>01may2013 stata replices "01may2013 invalid name" …
Reshape long to wide errorHello stateliest, Im having trouble trying to reshape my data set from long-wide. My code can be fou…
Insufficient observations for fixed effects regression using xtsetHi, My Stata version is 13.1. I am trying some small scale fixed effects regression to test if my ma…
Finding the response rate to questionnaireDear Statalist, I have a survey data about the respondents' beverage intake information across mult…
How do I drop dates later than 01.may 2013When I write: drop if=>01may2013 stata replices "01may2013 invalid name" …
Subscribe to:
Post Comments (Atom)
0 Response to Continuous vs binary independent variable in logistic regression
Post a Comment