Signal Discrimination Model (SDM) by Oberauer (2023)

Usage

sdm(resp_error, version = "simple", ...)

sdmSimple(resp_error, version = "simple", ...)

Arguments

resp_error: The name of the variable in the dataset containing the response error. The response error should code the response relative to the to-be-recalled target in radians. You can transform the response error in degrees to radians using the deg2rad function.
version: Character. The version of the model to use. Currently only "simple" is supported.
...: used internally for testing, ignore it

Value

An object of class bmmodel

Details

see the online article for a detailed description of the model and how to use it. * Domain: Visual working memory

Task: Continuous reproduction
Name: Signal Discrimination Model (SDM) by Oberauer (2023)
Citation:
- Oberauer, K. (2023). Measurement models for visual working memory - A factorial model comparison. Psychological Review, 130(3), 841-852
Version: simple
Requirements:
- The response variable should be in radians and represent the angular error relative to the target
Parameters:
- mu: Location parameter of the SDM distribution (in radians; by default fixed internally to 0)
- c: Memory strength parameter of the SDM distribution
- kappa: Precision parameter of the SDM distribution
Fixed parameters:
- mu = 0
Default parameter links:
- mu = tan_half; c = log; kappa = log
Default priors:
- mu:
  - main: student_t(1, 0, 1)
- kappa:
  - main: student_t(5, 1.75, 0.75)
  - effects: normal(0, 1)
- c:
  - main: student_t(5, 2, 0.75)
  - effects: normal(0, 1)

Examples

if (FALSE) { # isTRUE(Sys.getenv("BMM_EXAMPLES"))
# simulate data from the model
dat <- data.frame(y = rsdm(n = 1000, c = 4, kappa = 3))

# specify formula
ff <- bmf(c ~ 1,
          kappa ~ 1)

# specify the model
fit <- bmm(formula = ff,
           data = dat,
           model = sdm(resp_error = 'y'),
           cores = 4,
           backend = 'cmdstanr')
}