Hi,
I am working with a linear model where my outcome is a binary variable (selected) ranging 0 or 1. I have two types of predictors in my model and am wondering if the interpretation for each of the following is correct:
1. count variable (population) coefficient = 1.58e-10 --> A one unit increase in the population (a one person increase) is associated with a 0.000000000158% increase in the probability of being selected.
2. a proportion (proportion of older residents, ex. 0.45) coefficient= 5.43e-1 --> A one percent increase in the proportion of older residents is associated with a 5.43% point increase in the probability of being selected.
I am working with a linear model where my outcome is a binary variable (selected) ranging 0 or 1. I have two types of predictors in my model and am wondering if the interpretation for each of the following is correct:
1. count variable (population) coefficient = 1.58e-10 --> A one unit increase in the population (a one person increase) is associated with a 0.000000000158% increase in the probability of being selected.
2. a proportion (proportion of older residents, ex. 0.45) coefficient= 5.43e-1 --> A one percent increase in the proportion of older residents is associated with a 5.43% point increase in the probability of being selected.
