plot_ss_if: Plot Inhibition Functions

In EMC2: Bayesian Hierarchical Analysis of Cognitive Models of Choice

Plot Inhibition Functions

Description

Plots panels of the inhibition functions (probability of responding; Pr(R)) for each level of specified factors of stop-signal data as a function of user-defined SSD bins/categories. Optionally, posterior and/or prior predictive inhibition functions can be overlaid.

Usage

plot_ss_if(
  input,
  post_predict = NULL,
  prior_predict = NULL,
  probs = seq(0, 1, length.out = 5),
  factors = NULL,
  within_plot = NULL,
  use_global_quantiles = FALSE,
  subject = NULL,
  quants = c(0.025, 0.975),
  functions = NULL,
  n_cores = 1,
  n_post = 50,
  layout = NA,
  to_plot = c("data", "posterior", "prior")[1:2],
  use_lim = c("data", "posterior", "prior")[1:2],
  legendpos = c("topleft", "bottomright"),
  posterior_args = list(),
  prior_args = list(),
  ...
)

Arguments

input	Either an emc object or a stop-signal data frame, or a list of such objects. SSD column in data required.
post_predict	Optional posterior predictive data (matching columns) or list thereof.
prior_predict	Optional prior predictive data (matching columns) or list thereof.
probs	Numeric vector of probabilities with values on the unit interval that defines SSD bins/categories.
factors	Character vector of factor names to aggregate over; defaults to plotting full data set ungrouped by factors if NULL.
within_plot	Character indicating factor for which inhibition functions are plotted in the same panel
use_global_quantiles	If set to TRUE, SSDs are pooled over participants before calculating percentiles, so the same absolute SSD range is used to get Pr(R) for each participant, and then these probabilities are averaged over participants.
subject	Subset the data to a single subject (by index or name).
quants	Numeric vector of credible interval bounds (e.g. c(0.025, 0.975)).
functions	A function (or list of functions) that create new columns in the datasets or predictives
n_cores	Number of CPU cores to use if generating predictives from an emc object.
n_post	Number of posterior draws to simulate if needed for predictives.
layout	Numeric vector used in par(mfrow=...); use NA for auto-layout.
to_plot	Character vector: any of "data", "posterior", "prior".
use_lim	Character vector controlling which source(s) define axis limits
legendpos	Character vector controlling the positions of the legends
posterior_args	Optional list of graphical parameters for posterior lines/ribbons.
prior_args	Optional list of graphical parameters for prior lines/ribbons.
...	Other graphical parameters for the real data lines.

Details

Per default, the SSD-categories are defined in terms of the percentiles of the SSD distribution for each participant, and then averaged over participants (see use_global_quantiles).

If credible regions are not plotted, the data is plotted with error bars (plus/minus the standard error per SSD bin/category)

Value

Returns NULL invisibly

EMC2 documentation built on Dec. 2, 2025, 9:06 a.m.