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Confidence intervals for a frozen-margin association

Source: R/associate-pairs.R
confint.drm_pair_association.Rd

For admitted fixed-effect complete-pair association routes, vcov() returns the association-coefficient block of the two-stage Godambe sandwich and this method returns corresponding Wald intervals. type = "alpha" returns the coefficient-scale intervals. For an intercept-only association, type = "eta" monotonically transforms its link-scale limits to the bounded latent-association scale. A covariate-varying association has no single eta; use predict.drm_pair_association() with newdata for row-specific eta uncertainty. Every route is interval-feasible when its fit-specific covariance diagnostics pass. Coverage evidence currently promotes only the retained Bernoulli x ordinary-NB2 intercept domain to inference-ready with caveats; other routes receive an experimental-coverage warning.

Usage

# S3 method for class 'drm_pair_association'
confint(object, parm = NULL, level = 0.95, type = c("alpha", "eta"), ...)

Arguments

object

A fitted drm_pair_association object.

parm

Association coefficients to include. NULL (the default) or "alpha" selects all association coefficients; a numeric or character subset may also be supplied.

level

Confidence level in (0, 1).

type

"alpha" for coefficient-scale intervals or "eta" for the bounded latent association of an intercept-only model.

...

Reserved for future options.

Value

A matrix with Wald confidence limits on the requested scale.

See also

vcov(), predict.drm_pair_association()

Examples

if (FALSE) { # \dontrun{
set.seed(20260801)
dat <- data.frame(x = rnorm(100))
z_1 <- rnorm(100)
z_2 <- 0.35 * z_1 + sqrt(1 - 0.35^2) * rnorm(100)
dat$continuous <- 0.2 + 0.4 * dat$x + z_1
dat$binary <- as.integer(z_2 > qnorm(0.55))
assoc <- biv_associate(
  bf(mu = continuous ~ x, sigma = ~ 1),
  bf(mu = binary ~ x),
  family = list(gaussian(), binomial()), data = dat
)
confint(assoc, type = "eta")
} # }