Empirical RIR Distribution
Usage
konfound_empdist(
model,
target_var,
reps = 1000,
method = c("search", "direct"),
k = NULL,
alpha = 0.05,
seed = 123,
sign_flip_nullifies = TRUE,
engine = "auto",
get_test = NULL,
case_info = NULL,
verbose = FALSE,
progress = FALSE
)Arguments
- model
Fitted lm or glm object (must have model = TRUE)
- target_var
Name of the focal predictor coefficient
- reps
Number of simulation replications
- method
Either "direct" (fast, LM only) or "search" (original, LM/GLM)
- k
Override replacement count (default: k_cf). Only used for method="direct".
- alpha
Significance level for nullification decision
- seed
Random seed for reproducibility
- sign_flip_nullifies
If TRUE, sign reversal counts as nullification
- engine
For method="search": "auto", "fast", or "slow"
- get_test
For method="search": custom test extractor function
- case_info
Output from label_cases(). When provided with method="search", enables per-rep composition tracking (supporter fraction, etc.) and unlocks the stacked composition plot.
- verbose
Print detailed progress messages
- progress
Print progress every 100 reps