Description
Simulated Stop Signal Task Data.
Description
Stop signal task data of go and stop trials is generated per participant. The simulation process is based on the generally non-independent horse race model and fixed stop signal delay or tracking method. Each of go and stop process is assumed having exponentially modified Gaussian(ExG) or Shifted Wald (SW) distributions. The output data can be converted to 'BEESTS' software input data enabling researchers to test and evaluate various brain stopping processes manifested by ExG or SW distributional parameters of interest. Methods are described in: Soltanifar M (2020) <https://hdl.handle.net/1807/101208>, Matzke D, Love J, Wiecki TV, Brown SD, Logan GD and Wagenmakers E-J (2013) <doi:10.3389/fpsyg.2013.00918>, Logan GD, Van Zandt T, Verbruggen F, Wagenmakers EJ. (2014) <doi:10.1037/a0035230>.
README.md
README
Mohsen Soltanifar 2023-JAN-04
SimSST
The goal of SimSST is to simulate stop signal task data based on fixed ssd method and the tracking method.
Installation
You can install the development version of SimSST with:
library(gamlss.dist)
library(dplyr)
library(MASS)
library(SimSST)
Example: Simulation with fixed ssd method
This function takes in nine variables and produces a matrix of stop signal task data based on fixed ssd method
mySSTdata1 <-
simssfixed(
pid = c("FNLN1","FNLN1"),
block = c(1,2),
n = c(10,10),
m = c(4,4),
SSD.b = c(220,240),
dist.go = c("ExG","ExG"),
theta.go = as.matrix(rbind(c(440,90,90),c(440,90,90))),
dist.stop = c("ExG","ExG"),
theta.stop = as.matrix(rbind(c(120,80,70),c(120,80,70)))
)
mySSTdata1
Example: Simulation with tracking method
This function takes in nine variables and produces a matrix of stop signal task data based on tracking method
mySSTdata2 <-
simsstrack(
pid = c("FNLN1","FNLN1"),
block = c(1,2),
n = c(10,10),
m = c(4,4),
SSD.b = c(220,240),
dist.go = c("ExG","ExG"),
theta.go = as.matrix(rbind(c(440,90,90),c(440,90,90))),
dist.stop = c("ExG","ExG"),
theta.stop = as.matrix(rbind(c(120,80,70),c(120,80,70)))
)
mySSTdata2
Example: Simulating correlated SST data using general tracking method
This function takes in eleven variables and produces a matrix of stop signal task data based on the generalized tracking method.
mySSTdata3 <- simssgen(
pid = c("FNLN1", "FNLN2", "FNLN2"),
block = c(1,1,2),
n = c(50,100,150),
m = c(10,20,30),
SSD.b = c(200,220,240),
dist.go = c("ExG","ExG","ExG"),
theta.go = as.matrix(rbind(c(400,60,30),c(440,90,90),c(440,90,90))),
dist.stop = c("ExG","ExG","ExG"),
theta.stop = as.matrix(rbind(c(100,70,60),c(120,80,70),c(120,80,70))),
rho = c(0.35,0.45,0.45),
d = c(50,65,75))
mySSTdata3