postprocess: 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
)

Value

a "list" object of processed "regDIF" results

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.