generate_sim_data {RegDDM}R Documentation

Generate simulated binary decision data using DDM

Description

This function generates a simulated dataset under different configurations It can be used to test the performance and functionality of RegDDM. The outcome variable is y, which is influenced by different variables.

Usage

generate_sim_data(
  N = 30,
  n_each = 100,
  n_xvar = 2,
  beta_0 = 0,
  beta_c1 = 0,
  beta_c2 = 0,
  beta_v_0 = 0,
  beta_v_x1 = 0,
  beta_v_x2 = 0,
  sigma_y = 1,
  sigma_v = 0,
  y_family = "gaussian"
)

Arguments

N

Number of subjects.

n_each

Number of trials per subject

n_xvar

Number of trial-level variables influencing drift rate

beta_0

Intercept

beta_c1

Slope of c1

beta_c2

Slope of c2

beta_v_0

Slope of v_0

beta_v_x1

Slope of v_x1

beta_v_x2

Slope of v_x2

sigma_y

Standard deviation of error term of y, Only used when y_family is "gaussian"

sigma_v

Contaminant level for drift rate v.

y_family

Family of distribution of y. Can be either "gaussian", "bernoulli" or "poisson"

Value

A named list with four elements. data1_true and data2_true are true values of DDM parameters of each subject and trial. data1 and data2 removed those hidden variables.

Examples


sim_data = generate_sim_data()
sim_data$data1
sim_data$data2



[Package RegDDM version 1.1 Index]