Plot Method for sspLNIRT Objects

S3 method for the [base::plot()] generic, dispatched on objects of class `"sspLNIRT"` (returned by [optim_sample()], [comp_rmse()], or [get_sspLNIRT()]). The `type` argument selects the visualization:

`"estimation"` (default)

Per-parameter RMSE or bias as a function of the true (simulated) parameter value, faceted by parameter. See [plot_estimation()].

`"power_curve"`

Optimization trace as a log-log power curve plus the original-scale view, with the RMSE threshold and minimum \(N\) overlaid. Requires an [optim_sample()] result. See [plot_power_curve()].

Arguments specific to each `type` are passed through `...`.

Usage

# S3 method for class 'sspLNIRT'
plot(x, y = NULL, type = c("estimation", "power_curve"), ...)

Arguments

x

An object of class `"sspLNIRT"`.

y

Unused (required by the generic). Ignored with a warning if supplied.

type

Character. One of `"estimation"` or `"power_curve"`.

...

Additional arguments passed to the underlying plot helper. For `type = "estimation"`: `pars` (`"item"` / `"person"`), `y.val` (`"rmse"` / `"bias"`), `n.bins`. For `type = "power_curve"`: `out.par`, `thresh`.

Value

A [ggplot2::ggplot] object.

See also

[plot_estimation()], [plot_power_curve()], [theme_sspLNIRT()].

Examples

if (FALSE) { # \dontrun{
result <- get_sspLNIRT(
  thresh = 0.10, out.par = "alpha",
  K = 30, mu.alpha = 1,
  meanlog.sigma2 = log(0.6), rho = 0.2
)

# estimation accuracy
plot(result$object, type = "estimation", pars = "item", y.val = "rmse")

# power curve from the optimization trace
plot(result$object, type = "power_curve",
     out.par = "alpha", thresh = 0.10)
} # }