Case-Drop Stability for an LSA Fit

Resamples the underlying sequence data without replacement at a specified retention proportion, refits the engine on each subsample, and records which edges remain significant at the recipe's alpha threshold. Returns a per-edge "stability" proportion: the fraction of subsamples in which the edge was significant. Edges with stability >= min_stable (default 0.95) are flagged as robust.

Usage

stability_lsa(
  fit,
  R = 500L,
  proportion = 0.8,
  min_stable = 0.95,
  parallel = FALSE,
  n_cores = NULL,
  verbose = FALSE,
  ...
)

Arguments

fit

An lsa object returned by lsa().

R

Integer. Number of subsamples. Default 500.

proportion

Numeric in (0, 1). Fraction of cases retained per subsample. Default 0.8.

min_stable

Numeric in (0, 1). Stability threshold for the stable flag in the output edge frame. Default 0.95.

parallel

Logical. Use multi-core resampling. Default FALSE.

n_cores

Integer. Worker count when parallel = TRUE.

verbose

Logical. Print progress every 100 replicates.

...

Reserved.

Value

An object of class c("lsa_stability", "list") with:

edges

Tidy per-edge data frame with observed_sig (whether the cell was significant in the original fit), stability (fraction of subsamples in which the cell was significant), and stable (stability >= min_stable).

stability_matrix

R x K^2 0/1 matrix recording per-cell significance across replicates.

R, proportion, min_stable

Recipe metadata.

fit

Reference to the original fit.

See also

bootstrap_lsa(), permute_lsa()

Examples

# \donttest{
fit <- lsa(engagement, engine = "classical")
st <- stability_lsa(fit, R = 100)
head(as.data.frame(st))
#>         from      to observed_sig stability stable
#> 1     Active  Active         TRUE      1.00   TRUE
#> 2    Average  Active         TRUE      1.00   TRUE
#> 3 Disengaged  Active         TRUE      1.00   TRUE
#> 4     Active Average         TRUE      1.00   TRUE
#> 5    Average Average         TRUE      1.00   TRUE
#> 6 Disengaged Average        FALSE      0.27  FALSE
# }