I am stuck in a situation and the task is that I need to calculate proportion by comparing two columns.
The sample code is given below:
Fir <- glm(Drop_yn ~ Community + Age + Gender
+ Time_aus + Postcode_SEIFA + Edu_combine + Country_Q + Employ_comb +
House_cat + BMI_cate1 + WHtR_yn + High_BP + Weight_pc_cate
+ Chronic_con ,data = A2, family = "binomial",
control = list(maxit = 100))
From the above code it can be said that Drop_yn is the response variable and where the others are explanatory variables.
Drop_yn has two levels: Complete and DropOut.
The thing what I need to find out is that:
Depending on community which community has the highest percentage of Dropout.
What is the highest percentage of drop out depending on the increase or decrease in Age.
If any one gives me idea regarding how to solve the above queries will be very helpful.