Pivot-Style Statistical Tables for Large-Scale Assessment Data

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Documentation for package ‘LISTC’ version 1.0.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

as_long	Extract the tidy long form of a listc_table
as_wide	Extract the wide (row x column layout) form of a listc_table
lst_above	Add an above-cutoff indicator variable
lst_classify	Classify a variable into proficiency levels by cut scores
lst_config	Read and validate a LISTC run configuration
lst_config_template	Copy the Excel configuration template to a writable location
lst_data	Create a listc_data object
lst_derive	Add arbitrary derived variables (mutate-style)
lst_interpret	Rule-based plain-language interpretation of a listc_table
lst_join_person	Join person parameters onto a listc_data by id
lst_run	One-shot entry point: run a full LISTC analysis from a configuration
lst_table	Build a pivot-style statistical table
lst_to_excel	Export listc_table(s) to a formatted Excel workbook
lst_to_html	Export listc_table(s) as a standalone styled HTML report
lst_to_json	Export listc_table(s) as machine-readable JSON (for AI agents)
lst_validate	Validate a listc_data object
read_conquest_person	Read ConQuest person estimate output (WLE/EAP tables)
read_listc	Read sample data from common file formats
read_winsteps_pfile	Read a Winsteps PFILE (person parameter file)
st_count	Count and weighted-count statistics
st_level_prop	Proportions in proficiency levels
st_mean	Weighted mean statistic
st_option_dist	Weighted item option distribution (including missing rate)
st_prop_above	Proportion above a cutoff
st_pvalue	Weighted item p-value (proportion correct / mean score rate)
st_quantile	Weighted quantile statistic
st_sd	Weighted standard deviation
st_wcount	Count and weighted-count statistics