d_mu_gaussian: Partial derivatives for mean parameter of continuous items.

In regDIF: Regularized Differential Item Functioning

Partial derivatives for mean parameter of continuous items.

Description

Partial derivatives for mean parameter of continuous items.

Usage

d_mu_gaussian(
  parm,
  p_item,
  etable,
  theta,
  responses_item,
  pred_data,
  cov,
  samp_size,
  num_items,
  num_quad
)

Arguments

parm	Item parameter being maximized.
p_item	Vector of item parameters.
etable	E-table.
theta	Matrix of adaptive theta values.
responses_item	Vector of item responses.
pred_data	Matrix or dataframe of DIF and/or impact predictors.
cov	Covariate being maximized.
samp_size	Sample size in dataset.
num_items	Number of items in dataset.
num_quad	Number of quadrature points used for approximating the latent variable.

Value

a "list" of first and second partial derivatives for mean value of Gaussian item likelihood (to use with coordinate descent and univariate Newton-Raphson)

regDIF documentation built on May 29, 2024, 9:31 a.m.