Plot a Recovery Simulation

Draws the recovery curve of a simulate_recovery design: the chosen metric against sample size, one line per population loading and one panel per number of items per factor. This is the figure a validation paper reports, so the crossed design is worth running with enough replications for the curve to be stable.

Usage

# S3 method for class 'simulate_recovery'
plot(
  x,
  metric = c("recovery_rate", "sensitivity", "specificity", "convergence_rate",
    "mean_retained"),
  reference = 0.9,
  ...
)

Arguments

x

A simulate_recovery object.

metric

Which column of x$summary to draw: "recovery_rate" (default), "sensitivity", "specificity", "convergence_rate" or "mean_retained".

reference

Horizontal reference line, drawn only for the proportion metrics. Default 0.90; NULL removes it.

...

Ignored.

Value

A ggplot object.

See also

simulate_recovery

Examples

# \donttest{
sim <- simulate_recovery(n = 200, n_reps = 2, seed = 1)
#> Condition 1/1: N=200, lambda=0.65, items/factor=5 (17 items total)
#> 
  [                          ]   0% (0/2)  elapsed 0s  left ~?     
  [=============             ]  50% (1/2)  elapsed 9s  left ~9s     
  [==========================] 100% (2/2)  elapsed 12s  left ~0s     
plot(sim)
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?

plot(sim, metric = "sensitivity")
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?

# }