Visualizes the effect of covariates on structural parameters, as
declared with add_cov_association(), as a forest plot: one row per
(parameter, covariate, evaluation point), the point estimate and
interval as a ratio to the parameter's typical value, with a reference
line at 1.
This is the covariate-specific wrapper: it calls prm_cov() to
compute the effect-size table and xplot_forest() (a generic,
forest-plot-agnostic renderer, see its own documentation) to draw it.
cov_forest(
xpdb,
...,
type = "pilr",
region = NULL,
show_ref = TRUE,
log = TRUE,
forest_opts = list(),
title = "Covariate effects on model parameters | @run",
subtitle = "Ratio to typical parameter value; reference line at 1",
caption = "@dir",
tag = NULL,
.problem = NULL,
.subprob = NULL,
.method = NULL,
quiet
)The desired plot
<xp_xtras> object with covariate associations declared
via add_cov_association()
<dynamic-dots> Forwarded to
prm_cov() -- eg param ~ covariate selectors, ci_method,
probs, level, nsim.
Passed to xplot_forest(); defaults to 'pilr' (point +
interval + reference line + shaded reference region -- xplot_forest()'s
own defaults omit the line and region, since those are cov_forest()-
specific opinions, not generic ones).
Including "v" adds a violin/density layer of the raw simulation draws
behind each interval; this forces prm_cov(keep_draws = TRUE), which
in turn requires ci_method = "simulation" (the default) -- pass
ci_method = "delta" in ... together with type containing "v"
and it will error, since no draws exist for the delta method.
<numeric(2)> c(low, high) bounds for the shaded
reference region (type includes "r", the default); NULL
(default) falls back to c(0.8, 1.25), a common bioequivalence-style
"no relevant effect" band.
<logical> Include the reference row(s) (effect/
ci_low/ci_high always 1, by construction, for every reference
covariate value/level)? Defaults to TRUE; set FALSE to drop them
from the plot -- they carry no information beyond what the reference
line already shows, and cutting them can reduce clutter when there are
many covariates.
<logical> Log-scale the effect-ratio (x) axis? Defaults to
TRUE. Unlike most of the package's log arguments (eg
eta_vs_contcov()'s), this is a plain boolean rather than an
"x"/"y"/NULL axis-selector string -- cov_forest()'s orientation
isn't user-configurable, so the axis being logged is never ambiguous.
<list> Extra named arguments forwarded to
xplot_forest() (eg theme overrides), the same way pairs_opts
works for cov_grid()/eta_grid(). Rarely needed since the most
common override, type, is already its own argument.
Plot title
Plot subtitle
Plot caption
Plot tag
<numeric> Problem number
<numeric> Subprob number
<numeric> Method
Silence extra output
add_cov_association(), prm_cov(), xplot_forest()
# \donttest{
xpdb_x %>%
add_cov_association(
TVCL ~ power(CLCR, THETA7, ref = 64),
TVCL ~ catshift(SEX, THETA4, ref = 1)
) %>%
cov_forest()
# }
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