Hi everyone,

In the literature, I see an increasing use of hierarchical models to conduct a type of meta-analysis which involves analysing the raw data from across multiple studies in a model. In such models, a random effect is often included in the model to tell it about some structure across the data. For example within one study, data might be collected at 1 or more sites. If the data was included in the model at the site level (ie one row per site), then a random effect could be added for study ID.

I am working on a similar type of model and testing whether or not to include the study ID as a random effect. Within my data there are many studies which only have data for 1 site (so there is only 1 row per study), but some studies with between 2 and 18 sites.

I am only really interested in the fixed effects in the model, and I am not planning on making inferences about the random effects, only account for the fact that data from several sites came from the same study using the same method/team etc.

Including the random effect term in the model results in many high pareto-k values, but I read that the LOO may not be reliable in a mixed-effects model.

Is including a random effect for study even appropriate given that many studies only include data for 1 site?

Many thanks in advance.