# How to interpret coefficient of continuous predictor in logistic regression?

I have the following logistic regression in R:

glm(FundingSuccess ~ FundingGoal+ VentureTeamDiversity,
data = df, family = "binomial")


The VentureTeamDiversity variable is a Blau diversity index that ranges from 0 to 1. The regression coefficient of VentureTeamDiversity is 4.75 (p < 0.01). How do I interpret this coefficient? Basically, I am looking at understanding how much does an increase in VentureTeamDiversity by 10 percent affect the probability of successful funding (holding FundingGoal constant).

The coefficient $$\beta_1$$ can be interpreted as follows: $$e^{\beta_1t}$$ is the ratio of the odds of predicting a 1 after increasing $$X_1$$ by $$t$$ units to the odds of predicting a 1 while leaving $$X_1$$ alone.
In your specific scenario, $$e^{4.75(0.10)} = 1.049$$ means that the odds of getting funding after a 10% increase in VentureTeamDiversity is $$1.049$$ times the odds of getting funding without that increase.
• You could take the individual marginal effects at the observed values of $x$ and take the average over the estimation sample. This would produce a single number that gives you the average change in the probability of success associated with one additional unit of $x$ for everyone in the sample. Dec 10, 2021 at 1:29