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RCPA4 1.0.0

Initial release of the companion R package for Barry C. Edwards and Philip H. Pollock III, An R Companion to Political Analysis, Fourth Edition.

Datasets

• Added six classroom-ready datasets used throughout the fourth edition: anes, gss, states, world, debate, and students.
• Replaced the earlier nes teaching dataset with a curated subset of the 2024 American National Election Study, including documented recoded variables for textbook examples.
• Updated the General Social Survey, state, and world datasets with current observations and expanded political, social, demographic, and economic measures.
• Established maintained metadata sources that generate package data objects, variable documentation, and corresponding textbook appendix material.

Functions

• Updated the package’s teaching-oriented functions for descriptive statistics, data transformation, graphics, confidence intervals, hypothesis tests, comparisons, cross-tabulation, correlation, and regression.
• Improved support for optional sampling weights, data arguments, missing values, input validation, and consistent table and plot behavior.
• Added documented, reusable return values to the principal analysis functions. Regression functions retain standard model behavior, while auxiliary result tables are available through stable names.
• Improved handling of ordered factors and numeric-looking factor labels so that calculations use the displayed values where appropriate rather than internal factor codes.
• Expanded getC() support for common statistical and delimited data formats, compressed files, URLs, and native R files containing one or more objects.
• Redesigned helpC() to provide interactive access to function help, examples, datasets, variable metadata, plotting references, package settings, and chapter resources through R’s configured help system.
• Preserved familiar fourth-edition classroom workflows while improving error messages, P-value formatting, graphics-state restoration, and cross-platform plotting behavior.

Documentation and Testing

• Revised function documentation, argument descriptions, return-value details, and examples to agree with current behavior and use the fourth-edition datasets, including anes in place of nes.
• Updated textbook and online-resource references for the fourth edition.
• Added automated tests for core analysis paths, weighted and unweighted results, return structures, importing, interactive help, plotting behavior, dataset construction, and regression fixes.
• Added a separate checking harness for R code examples used in the textbook so package behavior and book instruction can be reviewed together.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.