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prLogisticDelta() now takes a fitted model
object as its first argument (instead of a formula + dataset).
This aligns with standard R modelling conventions and allows the same
function to handle all supported model types.cluster and pattern arguments of the
old prLogisticDelta() are replaced by
standardisation. Use
standardisation = "conditional" (default) or
standardisation = "marginal".Hmisc dependency has been removed (it was
unused).prLogistic S3 object rather than
a plain matrix, with print, summary,
coef, confint, and plot
methods.ref_continuous = "mean"). The old implementation only
supported binary (0/1) predictors.ref_values = list(var = value) to set the reference value
of any predictor. This overrides both automatic defaults and the model’s
contrast coding.prLogisticGEE()):
prevalence ratios for longitudinal / repeated-measures data fitted with
geepack::geeglm(). Robust (sandwich) variance is used
automatically.prLogisticSurvey()): prevalence ratios for data from
complex survey designs fitted with survey::svyglm().
Design-consistent variance is used automatically.plot.prLogistic(): base-R forest plot for quick
visualisation of PR estimates and confidence intervals.pr_marginal()
for models with more than one continuous covariate.pr.conditional() no longer crashes on
glmerMod objects that use lme4::fixef()
instead of @beta (the slot accessor was fragile across lme4
versions).. to avoid
namespace pollution.testthat (edition 3) test suite covering
utilities, delta method, bootstrap, GEE, and survey model types._pkgdown.yml configuration.R CMD check and automatic pkgdown deployment.lmer class with glmerMod for
compatibility with lme4 ≥ 1.0-4.NAMESPACE and ChangeLog files.mean with colMeans() in
pr.marginal().vcov() structure for S4 compatibility.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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