Sensitivity Path over Delta Grid — spliv_sensitivity

Runs spliv() repeatedly over a user-supplied delta_grid and returns a tidy sensitivity-path object. This is the recommended workflow for patterned or uniform sensitivity analysis: users should usually report how intervals change over a range of delta values rather than selecting one arbitrary sensitivity level.

Usage

spliv_sensitivity_path(
  formula,
  data,
  method = c("uci", "ltz"),
  delta_grid = seq(0, 0.2, by = 0.01),
  violation_pattern = NULL,
  stop_on_error = TRUE,
  ...
)

Arguments

formula: IV formula y ~ X | Z.
data: Data frame.
method: One of "uci" or "ltz". spliv_sensitivity_path() intentionally excludes confirmatory BPE.
delta_grid: Non-negative sensitivity grid. For UCI, each value d implies theta bounds [-d, +d].
violation_pattern: Optional spliv_pattern() object. If omitted, the path uses the package's backward-compatible uniform direct-effect pattern.
stop_on_error: Logical; if TRUE (default), stop on the first failed fit. If FALSE, record NA rows and store the error message in the returned error column.
...: Additional named arguments passed through to spliv(), such as fe, vcov, cluster, scale_instrument, or grid = list(level = 0.95).

Value

A data frame with class c("spliv_sensitivity_path", "data.frame"). The returned object includes path columns such as delta, method, estimate, conf_low, conf_high, contains_zero, and pattern metadata, plus attributes containing the original call, the supplied grid, and a tipping-point summary.

Examples

set.seed(5)
d <- data.frame(y = rnorm(80), x = rnorm(80), z = rnorm(80))
p <- spliv_sensitivity_path(y ~ x | z, d, method = "uci",
  delta_grid = c(0, 0.1), vcov = "hc1")
head(p)
#>          term delta method  estimate    conf_low conf_high contains_zero
#> 1 (Intercept)   0.0    uci  0.108665  -0.4663013 0.6836313          TRUE
#> 2           x   0.0    uci -1.979595  -6.9028208 2.9436307          TRUE
#> 3 (Intercept)   0.1    uci  0.108665  -0.6973215 1.0299906          TRUE
#> 4           x   0.1    uci -1.979595 -10.4825196 4.4046121          TRUE
#>            pattern_name pattern_type violation_pattern_used scale_instrument
#> 1 Uniform direct effect      uniform                  FALSE      residual_sd
#> 2 Uniform direct effect      uniform                  FALSE      residual_sd
#> 3 Uniform direct effect      uniform                  FALSE      residual_sd
#> 4 Uniform direct effect      uniform                  FALSE      residual_sd
#>   nobs se theta_min theta_max baseline_estimate baseline_conf_low
#> 1   80 NA       0.0       0.0          0.108665        -0.4663013
#> 2   80 NA       0.0       0.0         -1.979595        -6.9028208
#> 3   80 NA      -0.1       0.1          0.108665        -0.4663013
#> 4   80 NA      -0.1       0.1         -1.979595        -6.9028208
#>   baseline_conf_high crosses_baseline_sign significant_at_level error
#> 1          0.6836313                  TRUE                FALSE  <NA>
#> 2          2.9436307                  TRUE                FALSE  <NA>
#> 3          0.6836313                  TRUE                FALSE  <NA>
#> 4          2.9436307                  TRUE                FALSE  <NA>