---
title: "SimSST Examples"
author: "Mohsen Soltanifar"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{SimSST Examples}
  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{knitr::rmarkdown}
editor_options: 
  chunk_output_type: console
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```



# 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 descfarspkg with:

``` {r}
library(dplyr)
library(gamlss.dist)
library(MASS)
library(SimSST)
set.seed(1)
```

### Example: Fixed SSD method-based Simulation

```{r}
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: Tracking Method-based Simulation

```{r}
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
```

To convert tracking-based SimSST simulated data to BEESTS software input data, we have:

### Example: Converstion to BEESTs software format

```{r}
Datatemp2 <- mySSTdata2 
ss_presented <- recode(Datatemp2[,3], 'Stop' = "1", 'Go' = "0")
inhibited <- Datatemp2[,4]
ssd <- Datatemp2[,8]
rt <- Datatemp2[,5]
srrt <- Datatemp2[,7]
Data2 <- cbind.data.frame(ss_presented, inhibited, ssd, rt, srrt)
for(i in 1:20) if(Data2$inhibited[i]==0) Data2$rt[i] <- Data2$srrt[i]  
myBEESTSdata2 <- (Data2[,-5])[order(ss_presented),]
myBEESTSdata2
```

Once users reformat the simulated datasets to BEESTS dataset format, they may feed  the
BEESTS data to the BEESTS software to compute their plausible parameters (mu, sigma, tau). 

### Example: Simulating correlated SST data using general tracking method

```{r}
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
```
