trialWDM: Find by-trial Wiener Diffusion Model parameters
In akcochrane/ACmisc: Aaron Cochrane's miscellaneous functions

trialWDM

R Documentation

Find by-trial Wiener Diffusion Model parameters

Description

Estimates a set of Wiener Diffusion Model parameters for a vector of formatted data. Estimation uses RWiener::wdm and data must be formatted as a 1-dimensional vector according the to RWiener package (i.e., RT * 2 * (boundary=='upper' - 0.5) ).

Usage

trialWDM(
  dat,
  fit_DR = T,
  fit_BS = T,
  fit_NDT = T,
  fit_Bias = F,
  winsorize = NA
)

Arguments

`dat`	Response time vector. Positive values indicates upper-boundary while negative values indicate lower-boundary.
`fit_DR`	Logical or numeric scalar. If `TRUE` then drift rate is estimated for each trial, if `FALSE` only the overall parameter is estimated, and if numeric then the parameter is fixed to that value.
`fit_BS`	Logical or numeric scalar. If `TRUE` then boundary separation is estimated for each trial, if `FALSE` only the overall parameter is estimated, and if numeric then the parameter is fixed to that value.
`fit_NDT`	Logical or numeric scalar. If `TRUE` then non-decision time is estimated for each trial, if `FALSE` only the overall parameter is estimated, and if numeric then the parameter is fixed to that value.
`fit_Bias`	Logical or numeric scalar. If `TRUE` then bias is estimated for each trial, if `FALSE` only the overall parameter is estimated, and if numeric then the parameter is fixed to that value.
`winsorize`	Optional numeric scalar. If supplied, then all univariate values greater than number of MAD from the median are changed to be instead that number of MAD from the median (using `mad()` defaults).

Examples

## Not run: 
dat <- (rnorm(200,.2,.05) + rexp(200,1 / .2))*sample(c(-1,1,1),200,replace=T)
    m <- trialWDM(dat)
    
    m2 <- trialWDM(dat, fit_NDT = F , winsorize = 2)
    
    
## End(Not run)

akcochrane/ACmisc documentation built on Nov. 24, 2024, 11:22 a.m.