I came across this quote from a paper by Pool and Doris (2021): "The 18–24 age group reported the highest levels of food insecurity, with 27.6% reporting being food insecure, as opposed to 8.2% of over 65-year-olds (odds ratio (OR) 2.45, 95% confidence interval (CI): 1.05; 5.75)." I'd like to understand how they calculated the probability of over-65s which was their reference group in the logistic regression they ran.
Example logistic regression output:
Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -2.457415 0.221487 -11.095 < 2e-16 *** wave5 -0.510565 0.089884 -5.680 1.34e-08 *** wave7 -0.360667 0.089068 -4.049 5.14e-05 *** age_r2 -0.167394 0.163767 -1.022 0.306713 age_r3 -0.664402 0.171821 -3.867 0.000110 *** age_r4 -0.898270 0.161779 -5.552 2.82e-08 *** age_r5 -1.704232 0.162821 -10.467 < 2e-16 *** age_r6 -2.909736 0.183640 -15.845 < 2e-16 ***
I want to find out what the probability of the outcome variable is for the reference categories e.g. wave4 and age_r1. Apologies if this is straightforward but I've really struggled to find an answer. How can I do this in R?
Reference: Pool, U. and Dooris, M., 2021. Prevalence of food security in the UK measured by the Food Insecurity Experience Scale. Journal of Public Health,.