DstarM (version 0.1.0)

byParticipant: Helper function to do DstarM analyses by participant.

Description

A helper function to do run DstarM functions per participant. Supported functions are: estDstarM, estND, and estObserved.

Usage

byParticipant(data, resD, resND, argsEstDstarM = list(), argsEstND = list(), argsEstObserved = list(), uniqueArgs = FALSE)

Arguments

data

data.frame with a $id column. For other requirements, see estDstarM.

resD

list of decision models (all of class DstarM).

resND

list of nondecision models (all of class DstarM).

argsEstDstarM

Additional arguments for estDstarM.

argsEstND

Additional arguments for estND.

argsEstObserved

Additional arguments for estObserved.

uniqueArgs

Logical, are the additional arguments specified using one list for all participants or does the list of additional arguments contain lists with participant specific arguments?

Examples

## Not run: 
# library(DstarM)
# tt = seq(0, 5, .1)
# pars = c(.8, 2, .5, .5, .5, # condition 1
#          .8, 3, .5, .5, .5, # condition 2
#          .8, 4, .5, .5, .5) # condition 3
# pdfND = dbeta(tt, 10, 30)
# # simulate data for 2 participants
# n = 1.2e3
# data = rbind(simData(n = n, pars = pars, tt = tt, pdfND = pdfND),
#              simData(n = n, pars = pars, tt = tt, pdfND = pdfND))
# # add participant column
# data$pp = rep(1:2, each = n)
# # define restriction matrix
# restr = matrix(1:5, 5, 3)
# restr[2, -1] = 6:7 # allow drift rates to differ
# # fix variance parameters
# fixed = matrix(c('sz1', .5, 'sv1', .5), 2, 2)
# ## Run D*M analysis by pp
# resDpp = byParticipant(data = data,
#                        argsEstDstarM = list(tt = tt,
#                                             restr = restr,
#                                             fixed = fixed,
#                                             Optim = list(parallelType = 1)))
# coef(resDpp)
# plot(resDpp)
# resNDpp = byParticipant(resD = resDpp,
#                         argsEstND = list(Optim = list(parallelType = 1)))
# plot(resNDpp, xlim = 0:1)
# lines(tt, pdfND, col = 3, type = 'b')
# resObsPp = byParticipant(resD = resDpp,
#                          resND = resNDpp)
# plot(resObsPp)
# ## End(Not run)