I have a database with different variables which contains information such as age, date of vaccination, number of doses as well as the number of antibodies (which is my target variable). If the number of antibodies is under 100 and 10, the patient's antibodies level is regarded as low and very low accordingly. My goal is to create a model by which I would be able to determine WHEN a patient should receive his next vaccination based on these facts. Thus far I have only generated decision trees using R studio. My mathematical knowledge is limited to come up with a solution. How could this be achieved?
According to your question i can suggest you using logistic regression as you have two levels of dependent variable/Target Variable(DV) .Are your independent variable continuous or binary as well . You can also check similar post about binary DV (Prediction of a binary variable) and R tutorial on this (http://ww2.coastal.edu/kingw/statistics/R-tutorials/logistic.html)