computeInfoVal2IFC: Computes Informational Value

In rdotsch/rcicr: Reverse-Correlation Image-Classification Toolbox

Computes Informational Value

Description

Computes Informational Value for a single CI in a 2IFC task.

Usage

computeInfoVal2IFC(target_ci, rdata, iter = 10000, force_gen_ref_dist = FALSE)

Arguments

target_ci	A classification image object (list-type) as returned by generateCI
rdata	String pointing to .RData file that was created when stimuli were generated. This file contains the contrast parameters of all generated stimuli and possibly its corresponding reference distribution generated with generateReferenceDistribution().
iter	Number of iterations for the simulation of the reference distribution (only used if reference distribution is not already pre-generated and present in rdata file)
force_gen_ref_dist	Boolean specifying whether to override the default behavior to use pre-computed values for the reference distribution for specific task parameters and instead force to recompute the reference distribution (default: FALSE).

Details

The Informational Value metric can be considered as a z-score that quantifies the signal present in a classification image. The higher the Informational Value, the more signal. It is possible to use a cut-off such as z = 1.96 to select classification images with significant signal under alpha = 0.05.

Informational Value is computed by simulating random responding under identical task parameters to an empirical dataset (called the reference distribution). The metric quantifies how unlikely it is to observe these data under the null-hypothesis that there is no signal (i.e., that there is only random responding).

The simulation to compute the reference distribution takes a long time, and is only run locally when pre-computed values for the reference distribution matching the stimulus set in the .Rdata file have not been supplied by the rcicr package.

For more information see Brinkman, Goffin, Aarts, van Haren, & Dotsch (in prep).

Value

Informational value (z-score)

rdotsch/rcicr documentation built on Feb. 5, 2023, 10:15 p.m.