Hi All, I am doing a study in which I examine whether exposure to an agent (metabolite of a certain drug) can predict a longitudinal outcome in that patient. I am looking at patients in a treatment arm from a trial. Each patient may have taken a different quantity (dose) of the underlying drug. They then had a blood test checking for its active metabolite. Different patients will have different numbers of readings, depending on the duration for which they were in the study (dropped out, died, withdrawal etc) and therefore how many visits and subsequent blood tests they had. I want to see how exposure to the drug influences a longitudinal outcome, which itself is time-varying. What would be the best way to analyze this information? Presently, I have added together the total exposure values over however many visits the patient had, and done simple linear regression with the change in the longitudinal variable. I also calculated average exposure for each patient (total exposure/number of visits) and correlated this with the change in the longitudinal outcome (which itself I regressed over the amount of time patients were in the study). However, I feel this is a bit simplistic and am wondering if there is a better statistical method to analyze this question? At the least I feel I probably need to do some analysis with repeated measures. I hope this makes sense. Grateful for any help.
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