Plot Test Information Function

Displays the test information function (TIF), which shows the precision of measurement across the ability range. Higher information indicates more precise measurement. Requires ggplot2.

Usage

dpmirt_plot_info(
  fit,
  theta_range = c(-4, 4),
  n_points = 201,
  show_items = FALSE,
  show_density = TRUE,
  ...
)

Arguments

fit

A dpmirt_fit object from dpmirt.

theta_range

Numeric vector of length 2. Default: c(-4, 4).

n_points

Integer. Number of grid points. Default: 201.

show_items

Logical. Show individual item information curves. Default FALSE.

show_density

Logical. Overlay person ability density (scaled). Default TRUE.

...

Currently unused.

Value

A ggplot object.

Details

Fisher information for each item is:

Rasch: \(I_j(\theta) = P(1-P)\)

2PL: \(I_j(\theta) = \lambda^2 P(1-P)\)

3PL: \(I_j(\theta) = \lambda^2 \frac{(P - \delta)^2}{(1 - \delta)^2 P(1 - P)}\)

The test information function is the sum: \(I(\theta) = \sum_j I_j(\theta)\).

See also

plot.dpmirt_fit, dpmirt_plot_icc

Other visualization: dpmirt_plot_caterpillar(), dpmirt_plot_clusters(), dpmirt_plot_density(), dpmirt_plot_density_compare(), dpmirt_plot_dp_density(), dpmirt_plot_icc(), dpmirt_plot_items(), dpmirt_plot_parameter_trace(), dpmirt_plot_pp_check(), dpmirt_plot_trace(), dpmirt_plot_wright_map(), plot.dpmirt_estimates(), plot.dpmirt_fit(), plot.dpmirt_sim()

Examples

if (FALSE) { # \dontrun{
sim <- dpmirt_simulate(200, 20, model = "rasch", seed = 42)
fit <- dpmirt(sim$response, model = "rasch", prior = "normal",
              niter = 5000, nburnin = 1000, seed = 123)
dpmirt_plot_info(fit)
} # }