Multiplier-resampling (MR) estimates table (bootstrap-table format)

Renders the selected subgroup's MR de-biased estimate (forestsearch() with mr_inference = TRUE) in the same gt layout as the bias-corrected table produced by summarize_bootstrap_results(). The descriptive columns (sample size, medians/RMST or rates) and the naive effect do not depend on which de-biasing method was used, so they are inherited from a full-bootstrap (FB) result used as a template; the bias-corrected column is replaced with the MR values from fs$mr_inference – the de-biased estimate for the selected subgroup and, when MR was run with include_complement = TRUE, for the complement as well (otherwise the complement cell is marked, since MR de-biases the selected subgroup only).

Usage

mr_estimates_table(fs, boot_results, est.scale = "hr", digits = 2)

Arguments

fs

A forestsearch() result with a non-NULL mr_inference element.

boot_results

A forestsearch_bootstrap_dofuture() result used as the template for the descriptive columns, the naive effect, the complement row, and the subgroup footnote. Must contain FSsg_tab and SG_CIs.

est.scale

Character, "hr" or "1/hr"; passed to format_bootstrap_table(). Should match the scale of boot_results.

digits

Integer display precision (default 2), applied with the same reformatter summarize_bootstrap_results() uses so the two tables align.

Value

A gt table.

Details

The selected-subgroup row is matched by its bias-corrected string (boot_results$SG_CIs$H_bc) rather than by position, so the substitution is robust to row ordering. The MR de-biased confidence interval is a leading-order approximation of the full-bootstrap infinitesimal-jackknife interval – it comes from the IJ variance computed on the multiplier draws under ci_method = "ij" or "field" (the forest-search path defaults to "field", which adds the field bounds; the DINA and GRF paths default to "ij"), and from the subgroup robust SE only under ci_method = "wald". Either way the bias-corrected cell may differ slightly from the full bootstrap even when the naive effect matches exactly.

See also

forestsearch() for the mr_inference switch and the vocabulary section; fs_mr_inference() for the MR computation itself; forestsearch_bootstrap_dofuture() for the full bootstrap that supplies the template; fs_fdr_report() for harm-confirmation threshold sweeps; summarize_bootstrap_results(), format_bootstrap_table()