Define a hierarchical nesting structure

Specifies a hierarchical (nesting) level: each group-level unit belongs to exactly one nesting-level unit (e.g., governments within countries). hm() carries only the effect structure — random effects (RE = re(...), partial pooling) or fixed effects (FE = fe(...), no pooling). Fixed effects of unit-level covariates belong in the main formula, following the lme4/brms convention:


Y ~ gdp + hm(id = id(cid), RE = re(1 + gdp))   # like y ~ gdp + (1 + gdp | cid)

Usage

hm(id, RE = NULL, FE = NULL, labels = NULL, ...)

Arguments

id: An id object: id(hmid).
RE: Random effects: TRUE (shorthand for re(1)), an re object, or NULL. Slope variables are main-level columns varying within the nesting units. Default when neither RE nor FE is given: re(1).
FE: Fixed effects: a fe object (unit dummies via fe(1); unit-specific slopes via fe(1 + x); report per-unit estimates with fe(1, showFE = TRUE)). Mutually exclusive with RE.
labels: Unquoted variable name holding display labels for the nesting units (used when reporting per-unit fixed effects).
...: Not used; catches the removed type =, vars =, name =, showFE =, and ar = arguments (the last moved into the effects grammar: RE = re(1, ar = TRUE)) with a migration message.

Value

A bml_hm object.

Details

Cross-classified structures are modeled by including multiple hm() blocks. The old type = "RE"/"FE" and vars = arguments were removed: use RE = re(...) / FE = fe(...), and move unit-level covariates into the main formula (their coefficients are ordinary main-model coefficients).

References

Goldstein, H. (2011). Multilevel Statistical Models (4th ed.). Wiley.

Examples

if (FALSE) { # \dontrun{
hm(id = id(cid))                          # random intercepts (default)
hm(id = id(cid), RE = re(1 + x))          # random intercept + slope on x
hm(id = id(cid), FE = fe(1))              # country dummies (no pooling)
hm(id = id(cid), FE = fe(1, showFE = TRUE), labels = cname)
} # }