Interpreting the coefficients of a regression model depends on the type of model used:
Linear Regression: The coefficient represents the change in the outcome variable for a one-unit change in the predictor variable. Logistic Regression: The coefficient represents the log odds of the outcome occurring for a one-unit change in the predictor variable. Exponentiating the coefficient gives the odds ratio. Cox Model: The coefficient represents the log hazard ratio for a one-unit change in the predictor variable. Exponentiating the coefficient gives the hazard ratio. Poisson Regression: The coefficient represents the log rate ratio for a one-unit change in the predictor variable. Exponentiating the coefficient gives the rate ratio.
