Hi Noesi, Arndim

The slopes and the intercept are not so intuitive like linear regression but can still be interpreted.

The screenshot is not so clear. under the assumption that mer_ng_ml is the intercept. (or just for the example)

exp(0.0937267)=1.09825955

exp(0.1964993)=1.2171

**When all the values of the predictors (Xj) are zero:**

The odds of Y(1) in comparison to Y(0) is: **1.09825955**

**One unit increase in X1:**

Will increase the odds of Y(1) in comparison to Y(0) by **9.8%** (a.k.a. the odds will be multiplied by **1.09825955**).