I am having some issues with interpreting the results from a Poisson log linear model done in R. I will give my thoughts and it would be great if somebody would be kind enough to expand on it. I just need help with interpreting the coefficients.
I saw some interpretations online but almost all of use use the main effects or just one effect to explain. Also, the answers on stack exchange are not so simple that a layman could understand. Thank you in advance.
The data is from a paper titled "A Microeconometric Model of the Demand for Health Care and Health Insurance in Australia"
This is the back transformed data with intervals.
I drew some preliminary inferences,
We can infer from this that the expected number of visits by a doctor to a female at age zero is 0.23 (the intercept) with CI’s 0.195 and 0.271.
For every one extra male, the expected number of visits by a doctor increases by 0.45 with CI’s 0.349 and 0.576.
As age increases by one unit, the number of visits by a doctor increases by 1.009 for a female with CI’s 1.006 and 1.012.
Similarly, as age increases by one unit, the number of visits by a doctor if the patient is a male increases by 1.012 with CI’s 1.007 and 1.017.
Is this correct?