Marginal model

One way to get an estimate for such effects is through regression analysis.

In a typical multilevel model, there are level 1 & 2 residuals (R and U variables).

In a marginal model, we collapse over the level 1 & 2 residuals and thus marginalize (see also conditional probability) the joint distribution into a univariate normal distribution.

We then fit the marginal model to data.

Marginalized multilevel models and likelihood inference.