EMC2 (version 3.1.1)

make_emc: Make an emc Object

Description

Creates an emc object by combining the data, prior, and model specification into a emc object that is needed in fit().

Usage

make_emc(
  data,
  design,
  model = NULL,
  type = "standard",
  n_chains = 3,
  compress = TRUE,
  rt_resolution = 0.02,
  prior_list = NULL,
  par_groups = NULL,
  ...
)

Value

An uninitialized emc object

Arguments

data

A data frame, or a list of data frames. Needs to have the variable subjects as participant identifier.

design

A list with a pre-specified design, the output of design().

model

A model list. If none is supplied, the model specified in design() is used.

type

A string indicating whether to run a standard group-level, blocked, diagonal, factor, or single (i.e., non-hierarchical) model.

n_chains

An integer. Specifies the number of mcmc chains to be run (has to be more than 1 to compute rhat).

compress

A Boolean, if TRUE (i.e., the default), the data is compressed to speed up likelihood calculations.

rt_resolution

A double. Used for compression, response times will be binned based on this resolution.

prior_list

A named list containing the prior. Default prior created if NULL. For the default priors, see ?get_prior_{type}.

par_groups

A vector. Only to be specified with type blocked, e.g., c(1,1,1,2,2) means the covariances of the first three and of the last two parameters are estimated as two separate blocks.

...

Additional, optional arguments.

Examples

dat <- forstmann

# function that takes the lR factor (named diff in the following function) and
# returns a logical defining the correct response for each stimulus. In this
# case the match is simply such that the S factor equals the latent response factor.
matchfun <- function(d)d$S==d$lR

# design an "average and difference" contrast matrix
ADmat <- matrix(c(-1/2,1/2),ncol=1,dimnames=list(NULL,"diff"))

# specify design
design_LBABE <- design(data = dat,model=LBA,matchfun=matchfun,
formula=list(v~lM,sv~lM,B~E+lR,A~1,t0~1),
contrasts=list(v=list(lM=ADmat)),constants=c(sv=log(1)))

# specify priors
pmean <- c(v=1,v_lMdiff=1,sv_lMTRUE=log(.5), B=log(.5),B_Eneutral=log(1.5),
           B_Eaccuracy=log(2),B_lRright=0, A=log(0.25),t0=log(.2))
psd <- c(v=1,v_lMdiff=0.5,sv_lMTRUE=.5,
         B=0.3,B_Eneutral=0.3,B_Eaccuracy=0.3,B_lRright=0.3,A=0.4,t0=.5)
prior_LBABE <- prior(design_LBABE, type = 'standard',pmean=pmean,psd=psd)

# create emc object
LBABE <- make_emc(dat,design_LBABE,type="standard",  prior=prior_LBABE)