Aggregates feature-level test statistics across iterations using a Generalized Least Squares (GLS) framework,
assuming normality of the GLS estimator. Computes parametric p-values and summary statistics for each feature.
Usage
param_gls_summary(x, alpha = 0.05)
Arguments
- x
A data frame in long format with columns: `feature`, `iteration`, `T_obs`, `SE`, and `p_adj`.
- alpha
Numeric. Significance threshold used to compute the proportion of significant iterations.
Value
A data frame with feature, GLS estimate, SE, z-score, p-value, FDR-adjusted p-value, and prop_signif.