Large odds ratio in binary logistic regression/big scale difference of variables

#1
I'd like to ask for some help with a binary logistic regression. In SPSS I am building a binary logistic regression with 4 independent continuous variables(Sample size - 85). However, with one of the variables (Bicaudatus_index) I get a huge odds radio:


I think that I know where the problem is: the scale of this variable is very different than other variables:


As this variable is a ratio of two measurements, I try to multiply the variable 100 times and get a new variable, which odds ratio in the same regression seem to be within normal range.


However I don't know if it is appropriate to do that. If I multiply the variable not 100, but e.g. 150 times, I get odds ratios that are different from the ones that I get with 100.

Therefore, I want to ask what should I do in this case, is this method appropriate or do I need to interpret the results differently because of multiplication, or do I need a whole new approach. Help would be greatly appreciated :)
 

rogojel

TS Contributor
#2
hi,
this is quite natural and you are on the good track. The odds ratio tells us how the odds change if we change the X by one unit. Imagine we look at odds of heart attack vs. weight -the odds will definitely be greater if we measure the weight in 50 kg units as when we measure in grams (i.e the odds of a heart attack by a weight increase of 50kg vs. a weight increase of 1 g)
Regards
 
#3
hi,
this is quite natural and you are on the good track. The odds ratio tells us how the odds change if we change the X by one unit. Imagine we look at odds of heart attack vs. weight -the odds will definitely be greater if we measure the weight in 50 kg units as when we measure in grams (i.e the odds of a heart attack by a weight increase of 50kg vs. a weight increase of 1 g)
Regards
Thank you for your answer :). So as I understand, it is appropriate to multiply the varible e.i. 100 times to get a valid odds ratio, this way one just has to interpret it differently?
 

rogojel

TS Contributor
#4
I would phrase it differently - it is ok to re-scale the variable so that the change of 1 unit is of practical interest. E.g. neither a weight gain of 1 gram nor of 50kg is practically interesting, but maybe the effect of a change ofb500g or 1 kg would be.

regards