Audit a compiled model spec or fitted model

audit() returns the user-facing audit report attached to an mm_spec (pre-fit) or an mm_fit (post-fit). The text is rendered by the upstream Rust crate (the mixedmodels.model_audit_report schema's Display impl) — Rust authors the wording, R formats nothing. Routing every printed audit line through the upstream renderer is what enforces the R9 "no advice creep" contract: drift in scope notes / tone is visible in one place rather than scattered across R formatters.

Usage

audit(object, ...)

# Default S3 method
audit(object, ...)

# S3 method for class 'mm_compiled'
audit(object, ...)

Arguments

object: An mm_spec produced by compile_model() or an mm_fit from lmm()/glmm().
...: Reserved for future methods.

Value

An object of class mm_audit carrying:

text: the rendered report text (a single character string, newline-separated)
summary_text: the compact report rendered by the upstream ModelAuditReport::render_summary (Audit Summary plus the Requested Model section)
design_audit: the parsed design_audit field from the CompiledModelArtifact (random-term audits, fixed-effect rank, covariance kernel graph, ...) — NULL on uncompilable formulas
report: the parsed upstream ModelAuditReport v2, including Rust-authored random_term_cards for downstream explanation verbs
random_term_cards: the report's per-random-term cards, copied to the top level for convenient inspection
cross_card_constraints: report-level constraints between random-term cards
diagnostics: the parsed report diagnostics, falling back to artifact diagnostics when needed

print.mm_audit defaults to the compact upstream-rendered summary in summary_text. Use print(x, full = TRUE) for the complete upstream report stored in text.

Details

audit() accepts an mm_spec from compile_model() or an mm_fit from lmm()/glmm() and emits the report sections (Requested Model, Model State, Fixed/Random Effects, Information Budget, Dependence Paths, Parameterization Trace, Effective Covariance, Policy Recommendations, Optimizer, Inference, Diagnostics). Sections that depend on a fit (Optimizer / Inference) report not applicable before fitting on a pre-fit spec.

Errors

Raises an mm_schema_error if the supplied object does not carry a parsed artifact with the expected schema header.

Examples

if (FALSE) { # \dontrun{
df <- data.frame(
  y       = rnorm(20),
  x       = rnorm(20),
  subject = factor(rep(letters[1:5], each = 4))
)
audit(compile_model(y ~ x + (1 + x | subject), df))
} # }