Random effects model is based on the assumption that the studies are part of a large universe of similar studies. The relative risk estimate can be used to answer the question that will the intervention or the exposure be associated with the outcome studied (compare this with fixed effects model where the question was: did the studies show on average that the exposure or treatment associated with the outcome of interest?). However, a random effects model is computationally more intensive than a fixed effects model.