A fitted balancing result — balancing • balancing

balancing is the S7 object balance() returns. It carries the balancing weights, the resolved method and estimand, the covariate expansion recipe, a balance table, and the solver diagnostics. The raw data are not stored; the recipe carries what is needed to rebuild the constraint matrix.

Arguments

weights: The balancing weights, a bw vector.
method: The fitted balance_method specification.
estimand: The resolved estimand string.
exposure: The exposure column name.
exposure_type: The resolved exposure type.
exposure_levels: The exposure levels the fit weighted, as character strings in the order levels(factor(exposure)) gives: a factor's declared order for a factor exposure, and the values sorted in their own type otherwise, so a numeric dose of 9 and 10 orders 9 first. Levels no observation takes are dropped and do not appear. The first element is the reference level every contrast in ipw() is measured against. A continuous exposure carries no levels, so the vector is empty.
covariates: The covariate column names that contributed at least one retained constraint column, in selection order. The constraint expansion drops constant and aliased columns, and a covariate can be selected without contributing any column at all, so this records what the fit constrained rather than what was requested; the request itself stays in call. A fit whose balance comes from its objective rather than from constraints, such as energy or kernel balancing with no moment constraints, therefore records no covariates even though its objective reads every selected one.
focal_level: The focal exposure level for "att" and "atc", or NULL.
n: The number of observations.
constraints: The resolved balance_terms specification, or NULL.
recipe: The covariate expansion recipe, a list of per-column records.
balance_table: The achieved balance, one row per constraint term.
duals: Solver dual variables for diagnostics, or NULL.
coefficients: The fitted coefficients or dual variables, or NULL.
converged: Whether the solver met its convergence criterion.
iterations: The solver iteration count.
objective: The solved objective value.
solver_status: The solver that produced the result.
estimating_equations: The balancing_estimating_equations container, or NULL.
vcov: The covariance of the fit's own weight parameters, a p by p matrix named for them, or NULL. A covariance for those parameters comes from the stacked system an ipw() result assembles, so balance() leaves this empty and the result fills it in on the copy of the fit it stores, where stats::vcov() reads it back.
sampling_weights: The sampling weights, or NULL.
call: The originating call.

Value

A balancing object.