Broom: Tidy Summaries for Statistical Models in R

Broom is an R package authored by David P. Robinson that converts statistical analysis objects into tidy data frames. It provides three core verbs—tidy, glance, and augment—to extract model coefficients, goodness-of-fit statistics, and observation-level information, respectively. This facilitates consistent reporting, plotting, and batch analysis of many models.

Use Cases

• Generate standardized coefficient tables for reports based on the tidy() function.
• Compare model performance across many fitted models based on the glance() function's goodness-of-fit measures.
• Augment original data with model predictions and diagnostics for visualization based on the augment() function.
• Automate the creation of publication-ready plots from model outputs using the extracted tidy data.

Strengths

• Provides a consistent, programmatic interface for three distinct types of model information.
• Designed to work with a wide range of model types from R's statistical ecosystem.
• Integrates directly with the tidyverse workflow for data manipulation and visualization.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

David P. Robinson

Collection Method

Software package for R.

Time Range

null

Freshness

Last update date is unknown; freshness unverified.

Geography

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