I have a dataset of two patient and one healthy control group which I would like to compare (using R) with respect to a continuous outcome variable (each subjects is measured once). However the groups differ in age. In the context of the dataset the age effect is not of interest. My questions are:
What is the best way to account for the potentially confouding effect of age?
From what I know one could do this by either adding it as a covariate in the linear model or matching the samples with respect to age via usage of the propensity score. Which method is recommended in which context?
Is there an function to select subsamples of each group while matching groups with respect to age?