Convenience function to construct consonance functions given a point estimate and its standard error.
curve_from_se(estimate, se, measure = "mean", steps = 1000,
cores = getOption("mc.cores", 1L), table = TRUE)Point estimate.
Standard error of the estimate.
Type of measure: "mean" for differences (default), "ratio" for ratio measures (estimate should be on original scale).
Number of consonance levels to compute. Default is 1000.
Number of cores for parallel computation.
Logical. If TRUE (default), includes a summary table.
A list with class "concurve" containing the intervals dataframe, density dataframe, and optionally a summary table.
This function constructs consonance intervals using the normal approximation:
estimate +/- z * se where z varies across confidence levels.
For ratio measures, the function handles the log transformation internally.
curve_from_ratio() for constructing from CI bounds
curve_rev() for the underlying function
if (FALSE) { # \dontrun{
# Mean difference with SE
result <- curve_from_se(estimate = 2.5, se = 0.8, measure = "mean")
ggcurve(result[[1]], type = "c", nullvalue = TRUE)
# Odds ratio with SE (on log scale internally)
result <- curve_from_se(estimate = 1.5, se = 0.2, measure = "ratio")
ggcurve(result[[1]], type = "c", nullvalue = TRUE)
} # }