Computes hypothesis tests, contrasts, and small-sample corrections for
an estimate object. The arguments null, contrast, type, and
var.adj were previously available on estimate.default() and have
been moved here.
# S3 method for estimate
summary(
object,
contrast,
...,
null = 0,
level = 0.95,
type,
var.adj = 0.25,
df,
transform = NULL,
labels = NULL,
print = NULL
)an estimate object.
(optional) contrast matrix for the final Wald test. When
supplied together with null, tests \(H_0: B\theta = b_0\).
additional arguments passed to contr.
(optional) null hypothesis to test (default 0).
level of confidence limits (default 0.95)
type of small-sample correction. Requires the estimate to have
been computed with IC=TRUE (the default).
variance adjustment parameter for small-sample correction.
Requires the estimate to have been computed with IC=TRUE (the default).
degrees of freedom for t-based inference (default: NULL for
Gaussian approximation; when set, confidence intervals and p-values use the
t-distribution with df degrees of freedom)
(optional) function applied to the point estimates and
confidence interval bounds after inference is performed on the original
scale. Useful for variance-stabilizing transformations, e.g., compute CIs
on the atanh (Fisher z) scale and back-transform with tanh.
(optional) character vector with new parameter names
(optional) custom print function for the resulting
summary.estimate object
types of small-sample corrections:
"robust" (default): no correction.
"df": applies \(n/(n-p)\) correction (Mancl & DeRouen, 2001).
"mbn": Morel-Bokossa-Neerchal (2003) correction.
"hc3": leverage-adjusted HC3-type correction (blended with var.adj).
"hc4": Cribari-Neto (2004) leverage-adjusted correction.
The var.adj parameter controls the blending parameter for the HC3 leverage adjustment, by controls the weight between observation-level empirical leverage and the average leverage \(p/n\).
estimate.default()