Fit Meta-Analysis Models with Exact Contrasts — fmri_meta_fit

Low-level function that calls the C++ meta-analysis implementation and returns exact contrast statistics c' (X' W X)^(-1) c for provided contrasts.

Usage

fmri_meta_fit_contrasts(
  Y,
  V,
  X,
  Cmat,
  method = c("pm", "dl", "fe", "reml"),
  robust = c("none", "huber"),
  huber_c = 1.345,
  robust_iter = 2,
  n_threads = getOption("fmrireg.num_threads", 0)
)

Arguments

Y, V, X: See fmri_meta_fit
Cmat: Numeric matrix K x J (columns are contrasts over predictors)
method: Character scalar; meta-analysis method: "pm" (Paule-Mandel), "dl" (DerSimonian-Laird), "fe" (fixed-effects), or "reml" (REML, uses PM solver)
robust: Character scalar; robust estimation method: "none" or "huber"
huber_c: Numeric scalar; tuning constant for Huber M-estimator (default: 1.345). Smaller values provide more robust estimates but may reduce efficiency.
robust_iter: Integer scalar; number of IRLS iterations for robust estimation (default: 2)
n_threads: Integer scalar; number of OpenMP threads (0 = use all available)

Value

List with base meta outputs plus c_beta, c_se, c_z