Specify covariates for multiple-membership or hierarchical models

Helper function used within mm and hm to specify which variables should be included at each level of the model. Supports both free variables (with coefficients to be estimated) and fixed variables (with coefficients held constant using fix).

Usage

vars(...)

Arguments

...

Unquoted variable names from your data, combined using + (formula-style). Supports:

• Simple variables: vars(x + y)

• Interactions: vars(x * y) or vars(x:y)

• Transformations: vars(I(x^2)) or vars(I(x + y))

• Fixed coefficients: vars(fix(x, 1.0) + y)

Note: Numeric literals like 1, 0, or -1 are ignored (no intercept support in mm/hm blocks).

Value

A bml_vars object containing:

• formula: Formula object for use with model.matrix()

• free: Character vector of base variable names

• fixed: List of variables with fixed coefficients (if any)

Returns NULL if no variables are specified.

See also

fix, mm, hm

Examples

if (FALSE) { # \dontrun{
# Simple variable specification (formula-style with +)
vars(income + education)

# Single variable
vars(income)

# Interactions
vars(income * education)  # expands to income + education + income:education
vars(income:education)    # interaction only

# Transformations
vars(I(income^2))         # squared term
vars(income + I(income^2)) # linear and squared

# Mix free and fixed variables
vars(fix(exposure, 1.0) + income + education)

# Use in mm() specification
mm(
  id = id(pid, gid),
  vars = vars(rile + ipd),
  fn = fn(w ~ 1/n),
  RE = FALSE
)
} # }