summary-idealstan-method: Posterior Summaries for fitted 'idealstan' object

In idealstan: Robust Measurement with 'Stan'

Posterior Summaries for fitted idealstan object

Description

This function produces quantiles and standard deviations for the posterior samples of idealstan objects.

Usage

## S4 method for signature 'idealstan'
summary(
  object,
  pars = "ideal_pts",
  high_limit = 0.95,
  low_limit = 0.05,
  aggregated = TRUE,
  use_chain = NULL,
  cores = 1
)

Arguments

object	An idealstan object fitted by id_estimate
pars	Either 'ideal_pts' for person ideal points, 'items' for items/bills difficulty and discrimination parameters, and 'all' for all parameters in the model, including incidental parameters.
high_limit	A number between 0 and 1 reflecting the upper limit of the uncertainty interval (defaults to 0.95).
low_limit	A number between 0 and 1 reflecting the lower limit of the uncertainty interval (defaults to 0.05).
aggregated	Whether to return summaries of the posterior values or the full posterior samples. Defaults to TRUE.
use_chain	ID of a specific MCMC chain to use. Default (NULL) is all the chains and is recommended.
cores	Number of cores to use for parallel processing when summarizing item parameters. Defaults to 1 (no parallelization). Values greater than 1 use parallel::mclapply for faster computation with many items. Note that parallelization only works on Unix-like systems (Linux, macOS); on Windows, this parameter is ignored and single-core processing is used.

Value

A tibble data frame with parameters as rows and descriptive statistics as columns

Examples

data('senate114')
senate114$cast_code <- ifelse(senate114$cast_code=="Absent", NA,
                              as.integer(senate114$cast_code) - 1L)
sen_data <- id_make(senate114, outcome_disc='cast_code',
                    person_id='bioname', item_id='rollnumber',
                    group_id='party_code')
sen_est <- id_estimate(sen_data, model_type=1, fixtype='vb_full', use_method="pathfinder", ncores=4)
summary(sen_est, pars='ideal_pts')
summary(sen_est, pars='items')

idealstan documentation built on May 13, 2026, 1:08 a.m.