TreeBUGS: priorPredictive – R documentation

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priorPredictive

Prior Predictive Samples

Description

Samples full data sets (i.e., individual response frequencies) or group-level MPT parameters based on prior distribution for group-level parameters.

Usage

priorPredictive(
  prior,
  eqnfile,
  restrictions,
  numItems,
  level = "data",
  N = 1,
  M = 100,
  nCPU = 4
)

Arguments

`prior`	a named list defining the priors. For the traitMPT, the default is `list(mu = "dnorm(0,1)", xi="dunif(0,10)", V=diag(S), df=S+1)`, where S is the number of free parameters. For the betaMPT, the default is `list(alpha ="dgamma(1,.1)", beta = "dgamma(1,.1)")`. Note that the normal distribution `"dnorm(mu,prec)"` is parameterized as in JAGS by the mean and precision (= 1/variance).
`eqnfile`	The (relative or full) path to the file that specifies the MPT model (standard .eqn syntax). Note that category labels must start with a letter (different to multiTree) and match the column names of `data`. Alternatively, the EQN-equations can be provided within R as a character value (cf. `readEQN`). Note that the first line of an .eqn-file is reserved for comments and always ignored.
`restrictions`	Specifies which parameters should be (a) constant (e.g., `"a=b=.5"`) or (b) constrained to be identical (e.g., `"Do=Dn"`) or (c) treated as fixed effects (i.e., identical for all participants; `"a=b=FE"`). Either given as the path to a text file with restrictions per row or as a list of restrictions, e.g., `list("D1=D2","g=0.5")`. Note that numbers in .eqn-equations (e.g., `d(1-g).50`) are directly interpreted as equality constraints.
`numItems`	vector with the number of items per MPT tree (either named or assigned to alphabetically ordered tree labels)
`level`	either `"data"` (returns individual frequencies) or `"parameter"` (returns group-level MPT parameters; `M` and `numItems` are ignored)
`N`	number of participants per replication
`M`	number of prior predictive samples (i.e., data sets with `N` participants).
`nCPU`	number of CPUs used for parallel sampling. For large models and many participants, this may require a lot of memory.

Value

a list of M matrices with individual frequencies (rows=participants, columns=MPT categories). A single matrix is returned if M=1 or level="parameter".

Examples

eqnfile <- system.file("MPTmodels/2htm.eqn",
                       package="TreeBUGS")
### beta-MPT:
prior <- list(alpha="dgamma(1,.1)",
              beta="dgamma(1,.1)")

### prior-predictive frequencies:
priorPredictive(prior, eqnfile,
                restrictions=list("g=.5","Do=Dn"),
                numItems=c(50,50), N=10, M=1, nCPU=1)

### prior samples of group-level parameters:
priorPredictive(prior, eqnfile, level = "parameter",
                restrictions=list("g=.5","Do=Dn"),
                M=5, nCPU=1)

### latent-trait MPT
priorPredictive(prior=list(mu="dnorm(0,1)", xi="dunif(0,10)",
                           df=3, V=diag(2)),
                eqnfile, restrictions=list("g=.5"),
                numItems=c(50,50), N=10, M=1, nCPU=1)

TreeBUGS

Hierarchical Multinomial Processing Tree Modeling

v1.4.7

GPL-3

Authors

Daniel W. Heck [aut, cre] (<https://orcid.org/0000-0002-6302-9252>), Nina R. Arnold [aut, dtc], Denis Arnold [aut], Alexander Ly [ctb], Marius Barth [ctb] (<https://orcid.org/0000-0002-3421-6665>)

Initial release

2021-01-08