Calculate E-values for LMTP Output — lmtp_evalue

This function takes the output from `margot_tab_lmtp()`, which contains estimates of treatment effects, and calculates E-values to assess the robustness of the estimates to potential unmeasured confounding. E-values quantify the minimum strength of association, on the risk ratio scale, that an unmeasured confounder would need to have with both the treatment and the outcome, to fully explain away the observed association. The function supports both risk differences (RD) and risk ratios (RR) scales.

Usage

lmtp_evalue_tab(x, delta = 1, sd = 1, scale = c("RD", "RR"))

Arguments

x: A data frame output from `margot_tab_lmtp()` containing the estimates of interest.
delta: The hypothesized increase in outcome, used only when `scale` is "RD". Default is 1.
sd: The standard deviation of the outcome, used only when `scale` is "RD". Default is 1.
scale: A character string indicating the scale of the estimate: "RD" for risk difference, or "RR" for risk ratio. Default is "RD".

Value

A data frame similar to `x`, with additional columns for E-Value and its lower bound, excluding the 'standard_error' column.

Examples

if (FALSE) { # \dontrun{
# Assuming 'tab_contrast_hours_charity_z_null' is a data frame output from `margot_lmtp_tab()`
lmtp_evalue_tab(tab_contrast_hours_charity_z_null, scale = "RD")
lmtp_evalue_tab(tab_contrast_hours_charity_z_null, scale = "RR")
} # }