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Simulated data for example model fitting

Source: R/data.R
example_data.Rd

A simulated data set of 1000 trials from a two-alternative forced choice task with 4 levels of confidence.

Usage

example_data()

Value

A tibble of 1000 observations containing the following columns:

  • trial: the trial number

  • stimulus: the stimulus presence (0 or 1)

  • response: the simulated type 1 response

  • confidence: the simulated type 2 response

  • correct: the accuracy of the simulated type 1 response

  • dprime, c, meta_dprime, M, meta_c2_0, meta_c2_1: the parameters of the model used for simulation

  • theta, theta_1, theta_2: the joint, type 1, and type 2 response probabilities of the model used for simulation

See also

sim_metad()

Examples

# Fit an empty model on the example data
# (remove empty=TRUE to actually fit the model)
fit_metad(N ~ 1, example_data(), empty = TRUE)
#> `hmetad` has inferred that there are K=4 confidence levels in the data. If this is incorrect, please set this manually using the argument `K=<K>`
#>  Family: metad__4__normal__absolute__multinomial 
#>   Links: mu = log 
#> Formula: N ~ 1 
#>    Data: data.aggregated (Number of observations: 1) 
#> 
#> The model does not contain posterior draws.