SimSST (version 0.0.5.2)

simssfixed: Simulatng SSRT data using fixed SSD methods

Description

Stop signal task data of go and stop trials is generated per participant. The fixed stop signal delay method with underlying exponentially modified Gaussian (ExG) or Shifted Wald (SW) distributions for each of go and stop process is applied. The output data can be converted to 'BEESTS' software input data enabling researchers to test and evaluate different distributional parameters of interest.

Usage

simssfixed(pid, block, n, m, SSD.b, dist.go, theta.go, dist.stop, theta.stop)

Value

matrix with sum(n) rows and 8 columns

Arguments

pid

character vector of size b of participant

block

numeric vector of size b blocks

n

numeric vector of size b of total number of trials

m

numeric vector of size b of total number of stops

SSD.b

numeric vector of size b of stop signal delay

dist.go

character vector of size b of distribution of go trials, either ExG or SW

theta.go

numeric matrix of size b by columns of mu.go, sigma.go, and tau.go

dist.stop

character vector of size b of distribution of stop.trials, either ExG or SW

theta.stop

numeric matrix of size b by columns of mu.stop, sigma.stop, and tau.stop

References

Gordon D. Logan. On the Ability to Inhibit Thought and Action: A User's Guide to the Stop Signal Paradigm. In D. Dagenbach, & T.H. Carr (Eds.), Inhibitory Process in Attention, Memory and Language. San Diego: Academic Press, 1994.

Dora Matzke, Jonathon Love, Thomas V. Wiecki, Scott D. Brown, and et al. Release the BEESTS: Bayesian Estimation of Ex-Gaussian Stop Signal Reaction Times Distributions. Frontiers in Psychology, 4: Article 918, 2013.

Mohsen Soltanifar. Stop Signal Reaction Times: New Estimations with Longitudinal, Bayesian and Time Series based Methods, PhD Dissertation, Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada, 2020.

Examples

mySSTdata1 <- simssfixed(
 pid = c("John.Smith","Jane.McDonald","Jane.McDonald"),
 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))),
 block=c(1,1,2))
mySSTdata1