postprocess: Maximization step.
In regDIF: Regularized Differential Item Functioning

postprocess

R Documentation

Maximization step.

Description

Maximization step.

Usage

postprocess(
  estimates,
  item.data,
  pred.data,
  prox.data,
  item_data,
  pred_data,
  prox_data,
  mean_predictors,
  var_predictors,
  item_type,
  tau_vec,
  num_tau,
  alpha,
  pen,
  anchor,
  control,
  final_control,
  final,
  samp_size,
  num_responses,
  num_predictors,
  num_items,
  num_quad,
  NA_cases
)

Arguments

`estimates`	List of converged parameters.
`item.data`	User-given matrix or data.frame of DIF and/or impact predictors.
`pred.data`	User-given matrix or data.frame of item responses.
`prox.data`	User-given matrix or data.frame of observed proxy scores.
`item_data`	Processed matrix or data.frame of item responses.
`pred_data`	Processed matrix or data.frame of DIF and/or impact predictors.
`prox_data`	Processed matrix or data.frame of observed proxy scores.
`mean_predictors`	Possibly different matrix of predictors for the mean impact equation.
`var_predictors`	Possibly different matrix of predictors for the variance impact equation.
`item_type`	Optional character value or vector indicating the type of item to be modeled.
`tau_vec`	Optional numeric vector of tau values.
`num_tau`	Logical indicating whether the minimum tau value needs to be identified during the regDIF procedure.
`alpha`	Numeric value indicating the alpha parameter in the elastic net penalty function.
`pen`	Tuning parameter index.
`anchor`	Anchor item(s).
`control`	Optional list of user-defined control parameters
`final_control`	List of final control parameters.
`final`	List of model results.
`samp_size`	Sample size in dataset.
`num_responses`	Number of responses for each item.
`num_predictors`	Number of predictors.
`num_items`	Number of items in dataset.
`num_quad`	Number of quadrature points used for approximating the latent variable.
`NA_cases`	Logical vector indicating NA cases.