I'm fitting a logistic regression model in which my predictor of interest is a ratio of measurements in millimeters. Possible values for this ratio range from 0 to ~2.0, with typical values around 0.9-1.2. I want to measure the association between this variable and a binary outcome. I fit a model and obtained the following results:
Coefficients: Estimate Std.err Wald Pr(>|W|) (Intercept) -6.52673 1.09162 35.75 2.2e-09 *** x 0.91680 0.36187 6.42 0.011 * # OR = 2.5
I know that the generic way to interpret these results would be: "For a one unit increase in X, the odds of Y=1 increase by a factor of 2.5..." I keep getting hung up on the interpretation of this result, as a 1 unit change in x (e.g., from 0.6 to 1.6) would be a very extreme/physically impossible change for this particular ratio (which represents an index). Is there a way I should transform this variable or the results so that I can describe changes of 0.10 rather than 1.00?
Thanks in advance.