This is the summary of a fitted model on Titanic dataset in r
Estimate Std. Error z value Pr(>|z|)
(Intercept) 7.668775 0.641018 11.963 < 2e-16
Pclass -1.098189 0.137969 -7.960 1.72e-15
Sex:male -2.726408 0.194561 -14.013 < 2e-16
Age -0.039385 0.007773 -5.067 4.05e-07
Sibling -0.378646 0.106212 -3.565 0.000364
I want to interpret the coefficients for sibling and sex. I'm confused on the statements below, which is correct and which is incorrect:
For sibling:
Keeping all other predictors constant then, the odd ratio of survival for having an additional sibling is $e^{-0.38}=0.68$
Keeping all other predictors constant then, the log odd ratio of survival for having an additional sibling decreases by 0.38 units (what does it mean?)
Keeping all other predictors constant then, the odd ratio of survival for having an additional sibling decreases/increases by 0.68 units
Keeping all other predictors constant then, the odd ratio of survival for having an additional sibling is 0.68 times lower (less likely)
Keeping all other predictors constant then, the probability of survival for having an additional sibling is $sigmoid(-0.38)$ lower
When the other predictors are held constant, the odds ratio of survival between the given level (Male) and the reference level (Female) is -2.73 lower.
....
The coefficient is negative and the odd ratio is positive but below one, however I can't relate them to the response variable and how it affects the response variable.