The identification report (an executive one-pager)
Source:R/identification.R
proxy_identification_report.RdThe differentiator: a structured audit of what the decision model identifies, what it assumes, and what it cannot answer. Carries the estimand, the identification regime and its requirement, the overlap rate on the supplied population, the confounding-gap magnitude (the value at risk from unobserved confounding), and the explicit non-identification of the individual counterfactual law.
Arguments
- model
An uplift_model.
- newdata
A data frame carrying the covariate columns – the population the report is computed over.
- t1, t0
The treated and control treatment values. Default
1and0.
See also
proxy_confounding_gap(), proxy_overlap()
Other decision:
fit_uplift(),
gmm_cf_mean(),
gmm_cf_tail_prob(),
gmm_cf_variance(),
gmm_counterfactual(),
gmm_intervene(),
proxy_cate(),
proxy_confounding_gap(),
proxy_decide(),
proxy_overlap(),
proxy_policy_value(),
proxy_predict(),
proxy_regime_segments(),
proxy_retrospective_uplift(),
proxy_uplift(),
uplift_identification(),
uplift_model()
Examples
set.seed(1)
n <- 600L
x <- stats::rnorm(n)
t <- stats::rbinom(n, 1L, 0.5)
y <- 0.5 * t + x + stats::rnorm(n, sd = 0.5)
dat <- data.frame(y = y, t = t, x = x)
m <- fit_uplift(dat, "y", "t", "x", N = 2L, regime = "sample",
max_iter = 80L, seed = 1L)
proxy_identification_report(m, data.frame(x = stats::rnorm(100)))
#> == Identification report ==================================
#> Estimand : CATE / uplift: E[Y | do(T=t1), X] - E[Y | do(T=t0), X]
#> Assumption : ignorability
#> requires (Y(0), Y(1)) independent of T given X.
#> Regimes : K = 2 Outcome scale: continuous
#> Units : 100
#> Overlap : 99.0% of units adequately supported
#> Confounding gap (value at risk if a latent regime confounds):
#> mean |Delta| = 0.4842, max |Delta| = 0.572
#> NOT identified : the individual counterfactual law
#> (its variance and tail probabilities).
#> ===========================================================