Convert responses to quadrature form — mixed_subjects

Fits or accepts a 2PL model, computes posterior quadrature weights for each subject, and returns expected counts for mixed-subjects calibration. This is a lower-level helper; most analyses should call fit_mixed_subjects() or fit_mixed_subjects_split().

Usage

mixed_subjects_quadrature(
  resp,
  N_quad = 31,
  eps = 1e-15,
  iterlim = 1e+05,
  irt_pars = NULL,
  item_pars = NULL,
  quadrature = NULL,
  link_method = "mean_mean",
  ...
)

Arguments

resp: A response matrix with rows for subjects and columns for items.
N_quad: Number of quadrature nodes to compute. Kept for backward compatibility; prefer n_quad in new code.
eps: Retained for backward compatibility. Stable log computations are used instead of probability clipping.
iterlim: Maximum number of Newton-Raphson iterations passed to rmutil::gauss.hermite().
irt_pars: Optional target item parameters for mean-mean linking. This argument is kept for backward compatibility with earlier package versions.
item_pars: Optional item parameters. If omitted, a 2PL model is fit to resp using fit_2pl().
quadrature: Optional quadrature grid with theta and weight columns.
link_method: Linking method used when irt_pars is supplied.
...: Additional arguments passed to fit_2pl() when item_pars is omitted.

Value

A list with quad, counts, weights, irt_pars, quadrature, and theta.

Examples

pars <- data.frame(a = c(1, 1.2), d = c(0, -0.5))
resp <- matrix(c(1, 0, 0, 1), nrow = 2, byrow = TRUE)
q <- mixed_subjects_quadrature(resp, item_pars = pars, N_quad = 5)
names(q)
#> [1] "quad"       "counts"     "weights"    "resp"       "irt_pars"  
#> [6] "quadrature" "theta"