Pivot-Style Statistical Tables for Large-Scale Assessment Data
Overview
Turns assessment and survey sample data (demographics, scores, sampling weights, ability estimates with individual item response theory standard errors, replicate weights and plausible values) into fully customizable pivot-style statistical tables in which every cell carries a design-appropriate standard error. Provides weighted means, proportions above cut scores, proficiency-level percentages and quantiles; sampling variance via linearization, Woodruff (1952) doi:10.1080/01621459.1952.10483443 intervals for quantiles, or balanced repeated replication and jackknife replicate weights including Fay's method; measurement variance via delta-method propagation of individual standard errors or Rubin (1987) doi:10.1002/9780470316696 combination across plausible values. Imports data from 'CSV', 'Excel', 'SPSS', 'SAS', 'Stata' and item response theory software person files ('Winsteps', 'ConQuest'); a configuration-file interface serves non-programmers and automation; results export to formatted 'Excel', 'JSON' and standalone 'HTML' reports with rule-based plain-language interpretation.
First public release.
Core
lst_data()declares variable roles (id, groups, sampling weight, scores, ability estimates paired with individual IRT standard errors, item responses with scoring keys, replicate weights, plausible values).lst_table()builds Excel-pivot-style tables: free combination of row variables, column variables and cell statistics, with optional "Total" margins; results available as tidy long data (as_long()) or a formatted wide layout (as_wide()).- Statistics:
st_mean(),st_sd(),st_prop_above(),st_level_prop(),st_quantile(),st_count()/st_wcount(), item p-valuesst_pvalue()and option distributionsst_option_dist().
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- Every statistic reports a sampling standard error in every cell, including
st_option_dist(): each option share is computed as the weighted mean of its 0/1 indicator, so it reuses the same linearized and replicate-weight variance paths as the other statistics.
Variance engines
- Linearized sampling variance by default; Woodruff intervals for quantiles.
- Measurement variance propagated from individual IRT standard errors; probabilistic classification (
method = "prob") robust to misclassification near cut scores; empirical-Bayescorrection = "latent"for WLE/ML estimates. - Replicate weights (
rep_weights, methods fay/brr/jk1/jk2) for PISA/TIMSS-style designs, with prefix expansion such as"W_FSTR". - Plausible values (
pv = list(math = "PV#MATH")) with Rubin combination, composing with replicate weights.
Interfaces and output
- One-shot
lst_run()driven by YAML/JSON text or an Excel configuration workbook (lst_config_template()); JSON Schema and anllms.txtAPI digest ship ininst/for automated agents. - Importers for csv/tsv, Excel, SPSS/SAS/Stata (value labels preserved) and Winsteps/ConQuest person files.
- Export to styled Excel workbooks, machine-readable JSON and standalone HTML reports, each with rule-based plain-language interpretation.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE11 OK, 1 NOTE2026-08-01
- OK7 OK2026-07-29
Documentation
- Help pages
- 34 (7 internal)includes a package overview page
- Examples that run
- 100%27 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 95%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
- 50%
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Checks run against github.com/weiandata/listc on 2026-10-18.
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- Claude Opus 51 commit · Jul 2026
Dependencies
Installing LISTC adds 36 packages (22 with compiled code, 31 MB of source tarballs). Heaviest: stringi 11 MB, data.table 5.7 MB, readxl 2.1 MB.
Code & Tests
People & History
- 1.0.0Latest2026-07-28 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-28
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Copyright
- See file inst/COPYRIGHTS.
- Minimum R
- ≥ 4.1
- Download size
- 83 KB
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