I am trying to carry out a multivariate regression model where my main predictor is a continuous variable that changes over time, and my dependent variable is also a continuous variable that changes over time. I have already proven that my main predictor is an independent predictor significantly associated with my outcome of interest when examining this data cross-sectionally. I am interested in proving that these same two variables change together over time.
I have other covariates (discrete and continuous) I'd like to potentially include in the model as well. I have a variable for 'time points, 'that is tied to each value of my main predictor, as well as the raw dates of each time point tied to this main predictor. The time points are six months, 1 years, and 2 years. Not all patients have all time points.
I am working in R if you have interesting code that may help.