I need to interpret odds ratios from a multiple logistic regression predicting self esteem ("SelfEsteemHigh")from 2 predictor variables (agreeableness & conscientiousness).
> exp(coef(mlog2)) (Intercept) agreeableness 0.1999042 1.0607966 conscientiousness 1.2209377 > exp(confint(mlog2)) 2.5 % 97.5 % (Intercept) 0.007521561 4.390917 agreeableness 0.787426218 1.440916 conscientiousness 0.875694846 1.735260
These are the outcomes for odds ratios & 95% CI, the example for interpretation that was given to us was "A logistic regression predicting high stress from selfesteem (high / low) showed that students who had low selfesteem were expected to have 1.27 odds of being high stress, [95% CI 0.58 - 2.87]. Being in the high vs low self esteem group was associated with 0.08 times the odds of being high stress, [95% CI 0.02 - 0.30], p < .001. A graph of these results follows"
The issue is that my two predictor variables are continuous (not low/high) So I am unsure how to adapt my results to fit this interpretation example. please help!