compute_fcgdina_item_prob: Compute FCGDINA item-level endorsement probabilities

In ForceChoice: Forced-Choice Modeling Based on Item Response Theory and Cognitive Diagnostic Models

Compute FCGDINA item-level endorsement probabilities

Description

Computes statement endorsement probabilities for supplied attribute profiles under an FCGDINA item-level CDM parameterization.

Usage

compute_fcgdina_item_prob(
  alpha,
  delta.list,
  design.matrix.list,
  Q.matrix,
  gs = NULL,
  eps = 1e-12,
  link = c("identity", "logit")
)

Arguments

alpha	N \times D binary matrix of attribute profiles.
delta.list	List of per-item delta parameter vectors.
design.matrix.list	List of per-item design matrices.
Q.matrix	I \times D binary Q-matrix.
gs	Optional I \times 2 matrix of lower and upper probability bounds. If supplied, computed probabilities are clamped to gs[i, 1] and gs[i, 2] for item i.
eps	Numeric probability clamp used when gs = NULL. Default 1e-12.
link	Item probability link. "identity" uses p = X\delta; "logit" uses p = \mathrm{logit}^{-1}(X\delta). The latter is used by the Stan FCGDINA backend.

Details

The function maps each full attribute pattern in alpha to the reduced pattern required by each item-specific Q-vector, evaluates the corresponding design row, and multiplies by that item's delta vector. This function does not sample responses.

Value

An N \times I matrix of item endorsement probabilities.

See Also

model.FCGDINA, sim.data.FCGDINA

ForceChoice documentation built on Sept. 13, 2026, 1:06 a.m.