Fit Bayesian diagnostic classification models

Estimate diagnostic classification models (DCMs; also known as cognitive diagnostic models) using 'Stan'. Models can be estimated using Stan's optimizer, or full Markov chain Monte Carlo (MCMC).

Usage

dcm_estimate(
  dcm_spec,
  data,
  missing = NA,
  identifier = NULL,
  method = c("mcmc", "optim"),
  backend = getOption("measr.backend", "rstan"),
  file = NULL,
  file_refit = getOption("measr.file_refit", "never"),
  ...
)

Arguments

dcm_spec

A DCM specification created with dcm_specify().

data

Response data. A data frame with 1 row per respondent and 1 column per item.

missing

An R expression specifying how missing data in data is coded (e.g., NA, ".", -99, etc.). The default is NA.

identifier

Optional. Variable name of a column in data that contains respondent identifiers. NULL (the default) indicates that no identifiers are present in the data, and row numbers will be used as identifiers.

method

Estimation method. Options are "mcmc", which uses Stan's sampling method, or "optim", which uses Stan's optimizer.

backend

Character string naming the package to use as the backend for fitting the Stan model. Options are "rstan" (the default) or "cmdstanr". Can be set globally for the current R session via the "measr.backend" option (see options()). Details on the rstan and cmdstanr packages are available at https://mc-stan.org/rstan/ and https://mc-stan.org/cmdstanr/, respectively.

file

Either NULL (the default) or a character string. If a character string, the fitted model object is saved as an .rds object using saveRDS() using the supplied character string. The .rds extension is automatically added. If the specified file already exists, measr will load the previously saved model. Unless file_refit is specified, the model will not be refit.

file_refit

Controls when a saved model is refit. Options are "never", "always", and "on_change". Can be set globally for the current R session via the "measr.file_refit" option (see options()).

For "never" (the default), the fitted model is always loaded if the file exists, and model fitting is skipped.
For "always", the model is always refitted, regardless of whether or not file exists.
For "on_change", the model will be refit if the dcm_spec, data, method, or backend specified are different from that in the saved file.

...

Additional arguments passed to Stan.

For backend = "rstan", arguments are passed to rstan::sampling() or rstan::optimizing().
For backend = "cmdstanr", arguments are passed to the $sample() or $optimize() methods of the CmdStanModel class.

Value

A measrdcm object.

Examples

model_spec <- dcm_specify(qmatrix = dcmdata::mdm_qmatrix,
                          identifier = "item")
model <- dcm_estimate(dcm_spec = model_spec, data = dcmdata::mdm_data,
                      identifier = "respondent", method = "optim",
                      seed = 63277)