grt (version 0.1.0)

grg: General Random Guessing model

Description

General Random Guessing model

Usage

grg(response, fixed = FALSE, k = 2)

Arguments

response

A vector containing participant's classification responses.

fixed

logical. If TRUE, Fixed Random Guessing model is fitted. If FALSE, General Random Guessing model is fitted. see Details

k

numeric. the penalty per parameter to be used in calculating AIC. Default to 2.

Value

• a list object containing:
• par
  the fixed or estimated response bias
• logLik
  the log-likelihood of the model
• AIC
  Akaike's An Information Criterion for the fitted model

Details

The function assumes that there are two categories (e.g, A and B) to which each stimulus belongs.

Fixed Random Guessing model assumes that participant responded randomly without response bias; for each stimulus, probability of responding A and B is .5. There is no free parameters in this model (i.e., df = 0).

General Random Guessing model assumes that partiicpants responded randomly but is biased toward one response. The model estimates the response bias (df = 1).

References

Ashby, F. G., & Crossley, M. J. (2010). Interactions between declarative and procedural-learning categorization systems. Neurobiology of Learning and Memory, 94, 1-12.

See Also

glc, gqc

Examples

data(subjdemo_2d)
fit.grand <- grg(subjdemo_2d$response, fixed=FALSE)

fit.frand <- grg(subjdemo_2d$response, fixed=TRUE)