Hi.

I have a dataset of psychological measures from carers (n=254) of people with mental health patients. We are using regression analyses to explore predictors of experiencing distress in carers.

Some of the carers care for the same patient. In other words - researchers collected the data by asking patients if they could speak to their carers. In most cases, researchers spoke to 1 carer per patient. But they in some cases they recruited more (up to 4) per patient. As such the data are clustered. Approximately 150 patients have 1 carer. Approx. 50 have 2 carers. The remaining 2-3 have 3 or 4 carers. So the clusters are often small.

The data are hierarchical: multiple patients (lower level) per carer (higher level). But in most cases there is only 1 patient per carer.

Does this structure benefit from mixed effects/multi-level modelling or are cluster robust standard errors better?

thank you very much in advance!