Summarize and Plot Posterior Predictive Item-Restscore Associations

Postprocesses the output of item_restscore_statistic to produce a summary table and a slab plot comparing observed item-restscore gamma associations to the posterior predictive distribution.

Usage

item_restscore_post(item_restscore)

Arguments

item_restscore

A list as returned by item_restscore_statistic, containing at minimum:

result

A data frame with columns including item and summary statistics (first 5 columns are used).

draws

A data frame with columns item, gamma (observed gamma per draw), and gamma_rep (replicated gamma per draw).

Value

A list with two elements:

summary

A tibble with the first 5 columns of the result table, rounded to 3 decimal places and sorted by item.

plot

A ggplot object showing the posterior predictive distribution of replicated gamma (grey filled slab) with the observed gamma values overlaid as orange diamond points.

Details

The item-restscore gamma association measures the strength of the relationship between each item's responses and the rest score (total score excluding that item). Under good fit, the observed gamma should fall within the posterior predictive distribution.

The plot displays:

Grey slab

The posterior predictive distribution of replicated gamma values, shaded by 84\ interval levels.

Orange diamonds

The observed gamma values per draw, plotted as points on top of the slab.

Items where the observed gamma (orange) falls consistently outside the replicated distribution (grey) indicate poor fit in terms of item discrimination.

See also

item_restscore_statistic, infit_post.

Examples

if (FALSE) { # \dontrun{
library(brms)
library(ggplot2)

# Assuming fit_pcm is a fitted brmsfit object
irs <- item_restscore_statistic(fit_pcm)

result <- item_restscore_post(irs)
result$summary
result$plot
} # }