Dear all,
I would like to use some continuous variables to see if I can predict a certain behavior (such as "fallers-people who had a history of falls" versus "non-fallers").
My dependent variable is "Group" (0=non-fallers, 1=fallers).
For the independent variables, I use couple of continuous measures.
Since the absolute values of my independent variables would affect the "unit odds ratio" (although the "range" odds ratio would be the same), how should I choose the "unit" of the independent variables (such as "meters versus centi-meters")?
For example, If I input my data in centi-meters, I would have the unit odds ratio as 0.6. But if I input my data in meters, then I would have the unit odds ratio as 0.002.
Also, if I would like to compare the unit odds ratio among different independent variables, how should I do to make it fair since their absolute values are very different due to different scales/units?
Moreover, if the distribution of a certain independent variables is not normal, should I transform my data first (such as log transform) before running the logistic regression?
thank you in advance!
Hi Peggy,
why not standardizing all scales to mean 0, variance 1 or even keeping the mean and shrinking / expanding all to the same variance? Then you should get the same beta for centimeters and meters. And sure, for skewed distributions apply the log transform before.
Hans
Thank you so much Hans!
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