I am trying to asses the odds of people staying in a program given their backgrounds following these instructions. One of the variables I am looking at is age, which I split into five groups. I have run a test using the formula:
mylogit15 <- glm(Stay_in_Progams ~ Age.Group + Prior_Experience,
data = mydata, family = "binomial")
The results of the test are clear enough, except I am missing the first and third age groups. This is what they look like:
Coefficients:
Estimate Std. Error z-value Pr(>|z|)
(Intercept) -.298 1.173 -1.98 .047
Age Group2 1.201 1.243 0.966 .333
Age Group4 2.735 1.486 1.840 .065
Age Group5 1.636 1.673 0.965 .334
Prior_Exp 3.546 1.234 2.735 .006
Thank you for taking the time to read this and help me out!