rcces

rcces is a set of helper functions to format, clean, and operationalize variables used in Shiro Kuriwaki's CCES-based representation research. It supports the data pipeline and analysis scripts in those replication packages.

Functions

Reshaping and cleaning survey data

• melt_cces() — Reshape wide CCES data (one column per question) into long format (one row per respondent-question).
• parse_qlabel() — Parse camelCase question labels into readable text for plotting (e.g., "RepealACA2017" to "Repeal ACA 2017").
• std_short_party() — Standardize party labels to short codes ("D", "R", etc.).
• std_party_prcp_varname() — Standardize party perception variable names across CCES years.

Computing agreement and opinion

• dyad_agrmt() — Compute dyadic agreement (+1/0/-1) between a constituent's survey response and their legislator's roll call vote.
• code_threeway() — Code agreement between any two Y/N/DK or D/R/I variables as +1, 0, or -1.
• question_split() / issue_split() — Compute proportion supporting "Yes" by question or by issue (pooling across years).
• prop_seats() — Compute the proportion of districts with majority support, with a probabilistic adjustment for sampling uncertainty.

Formatting and labeling

• vartab() — Recreate Stata's variable table from a haven-imported data frame.
• attach_varlab() — Attach Stata-style variable labels to columns for export.
• cmfmtW() — Format a number with commas and write it to a .tex file for LaTeX inclusion.
• H_to_house() / H_to_cd() / H_to_rep() — Recode "H"/"S" chamber codes to readable labels.

Installation

The package is not on CRAN. Install from GitHub:

pak::pkg_install("kuriwaki/rcces")

Related Packages

• ccesMRPprep — Functions to download and standardize CCES data for MRP.
• ccesMRPrun — Functions to fit multilevel models and poststratify.
• cces_cumulative — Code for the cumulative Common Content dataset.