Create a publication-ready sensitivity-analysis table — tbl

Formats method-comparison results from twophase_sensitivity() with methods in rows and one group of columns per outcome. By default, the function returns a gtsummary object with outcome spanning headers. A plain data frame can be requested for downstream custom formatting.

Usage

tbl_sensitivity(
  x,
  estimate_digits = 3L,
  p_digits = 3L,
  include_se = FALSE,
  method_labels = NULL,
  outcome_labels = NULL,
  caption = NULL,
  output = c("gtsummary", "data.frame")
)

Arguments

x: A twophase_sensitivity object.
estimate_digits: Number of digits for estimates and confidence limits. The default is 3.
p_digits: Number of digits for p values.
include_se: Logical; include a separate standard-error column for each outcome.
method_labels: Optional named character vector used to relabel methods. Names should be package method labels such as "FCS-MI" or "AIPW".
outcome_labels: Optional character vector used to relabel outcomes. Supply either a named vector whose names are the outcome variable names or an unnamed vector in the same order as x$specification$outcome.
caption: Optional table caption. Markdown is supported for output = "gtsummary".
output: Output type: "gtsummary" (default) or "data.frame".

Value

A gtsummary object by default, or a formatted data frame when output = "data.frame".

Examples

dat <- twophase_example_data(n = 200, seed = 2026)
fit <- twophase_sensitivity(
  data = dat,
  outcome = "outcome1",
  exposure = "exposure",
  covariates = c("age", "sex"),
  phase2_covariates = c("marker1", "marker2", "marker3"),
  phase2 = "phase2",
  methods = c("naive", "cca", "ipw"),
  seed = 1001
)
tbl_sensitivity(fit, output = "data.frame")
#>   Method outcome1 Coefficient (95% CI) outcome1 P value
#> 1  Naive        0.407 (0.271 to 0.544)           <0.001
#> 2    CCA        0.235 (0.019 to 0.451)            0.033
#> 3    IPW        0.233 (0.023 to 0.444)            0.029