Creating predict function in a Poisson regression

Question

I have a data-set in which I need to perform a Poisson regression analysis of how number of visits to the doctor in the two week period varies as a function of age group (i.e.<30, between 30 and 50, and >50), sex and illness. Holding sex and number of illnesses constant at their mean values.

Here is a sample of my data:

 visits gender age illness
     1 female  19       1
     1 female  19       1
     1   male  19       3
     1   male  19       1
     1   male  19       2
     1 female  19       5
     1 female  19       4
     1 female  19       3
     1 female  19       2
     1   male  19       1

However, I do not know how to go about this as I don't know how to correctly input these groups. As I need to discover the predicted rates of visits to a doctor over a two week period for different age groups.

I know how to input the initial equation: glm(visits ~ age + gender + illness, data=DoctorVisits, family=poisson)

But I do not know how I would go about creating the predict function.

Answer 1

Say you want to predict for male 21 y/o and illness = 3

predict(your_glm, 
newdata = data.frame(gender = "male", age = 21, illness = 3),
type = "response")

Here you basically are creating a data frame with obseravations you want the predictions for inside the function. If you have several observations you want the prediction for then it may be more sensible to create the data frame separately first and then feed it to predict function, just swap "newdata=" to "data=".

type = "response" will give you the prediction in the same format as in glm, otherwise it will be log ods.