Hierarchical models are constructed by specifying different levels of the hierarchy. For example, a two-level model might include individual-level data (level 1) nested within group-level data (level 2). The general form of a two-level hierarchical model can be represented as:
Y_ij = β0 + β1X_ij + u_j + ε_ij
where: - Y_ij is the outcome for individual i in group j. - X_ij are the covariates. - β0 and β1 are fixed effects. - u_j is the random effect at the group level. - ε_ij is the residual error at the individual level.
