id_plot_ppc,idealstan-method

object

The output of the <code><a rd-options="" href="/link/id_post_pred?package=idealstan&version=0.7.1" data-mini-rdoc="idealstan::id_post_pred">id_post_pred</a></code> function on a fitted idealstan object

ppc_pred

A character vector of the person or group IDs 
over which to subset the predictive distribution

group

A character vector of item IDs to subset the posterior distribution

item

Other arguments passed on to <code><a rd-options="bayesplot" href="/link/ppc_bars?package=idealstan&version=0.7.1&to=bayesplot" data-mini-rdoc="bayesplot::ppc_bars">ppc_bars</a></code>

This function is the actual method for generating posterior distributions 
from a fitted <code>idealstan</code> model.

Offers item-response theory (IRT) ideal-point estimation for binary, ordinal, counts and continuous responses with time-varying and missing-data inference. Full and approximate Bayesian sampling with 'Stan' (<https://mc-stan.org/>).

Robert Kubinec

idealstan

Generalized IRT Ideal Point Models with 'Stan'

Jonah Gabry

Ben Goodrich

Trustees of Columbia University 

id_plot_ppc,idealstan-method function

The output of the <code><a rd-options='' href='id_post_pred'>id_post_pred</a></code> function on a fitted idealstan object

Other arguments passed on to <code><a rd-options='bayesplot' href='ppc_bars'>ppc_bars</a></code>

id_plot_ppc,idealstan-method: Plot Posterior Predictive Distribution for `idealstan` Objects

Description

Usage

Arguments