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model_card() is the entry point for acting on a fit. It returns everything explain() shows – equation, symbol dictionary, assumptions, notation and formula bridges, per-coefficient interpretations, factor-coding overview, variance components – and adds the act-on-it layer: extraction calls (R code to pull out blocks of the fit), recommended plots (one-line text recipes), and the marginal estimates (group_means() / group_slopes() / group_contrasts()).

Use explain() when you only want to understand the model; use model_card() when you also want a quick reference of what to extract, what to plot, and how the groups compare.

The bundle is a plain list; print it at the console for a structured walkthrough, or knit it inside a Quarto / R Markdown document for a heading-and-table section per piece.

Usage

model_card(x, ...)

Arguments

x

A symbolized_model (output of symbolize()).

...

Reserved for future use.

Value

A symbolizer_model_card (a list) with elements: meta, equation, symbols, assumptions, notation_bridge (and its deprecated alias bridge), formula_bridge, interpretation, factor_coding, variance_components (NULL when the model has no random effects), warnings, extraction_calls, recommended_plots, marginal_means (NULL when the model has no factors), marginal_slopes (NULL when no continuous-by-* interaction is present), and marginal_contrasts (NULL when the model has no factor).

See also

explain() for the understand-only bundle.

Examples

# model_card(symbolize(lm(mpg ~ wt, data = mtcars)))