postprocess | R Documentation |
Maximization step.
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 )
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. |
a "list"
object of processed "regDIF"
results
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