First public release; on CRAN since 2026-07-28.
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()).st_mean(), st_sd(), st_prop_above(),
st_level_prop(), st_quantile(), st_count()/st_wcount(), item
p-values st_pvalue() and option distributions st_option_dist().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.method = "prob") robust to
misclassification near cut scores; empirical-Bayes
correction = "latent" for WLE/ML estimates.rep_weights, methods fay/brr/jk1/jk2) for
PISA/TIMSS-style designs, with prefix expansion such as "W_FSTR".pv = list(math = "PV#MATH")) with Rubin
combination, composing with replicate weights.lst_run() driven by YAML/JSON text or an Excel
configuration workbook (lst_config_template()); JSON Schema and an
llms.txt API digest ship in inst/ for automated agents.