Nothing
r
est = est = feols(flipper_len ~ bill_len | species, penguins)
ggcoefplot(est, vcov = list("iid", "hc1", ~species))
keep
and drop
arguments now work correctly with a list of models.
Thanks to @femdias for the report. (#60)ggcoefplot
or ggiplot
then the original order is preserved for grouping and facet behaviour (#63)ggplot2
dependency to v4.0.0 and update test snapshots. (#55, #59) fixest
dependency to v0.13.0 and update tests. (#58, #59) aggr_es(..., period = "diff")
convenience keyword argument allows
users to estimate the difference between the (mean) post- and pre-treatment
periods. Thanks to @FBrunamonti for the suggestion. (#52).svglite
dependency version and update test snapshots. (#51) aggr_es
objects. (#43)ggh4x
dependency with legendry
. (#41 @teunbrand)First CRAN release!
aggr_es
function now supports numeric sequences for aggregating a
specific subset of periods, in addition to the existing keyword strings like
"pre" or "post". This functionality also passes through to the higher order
plotting functions that call aggr_es
under the hood. For example,
ggiplot(est, aggr_eff = 6:8)
. (#33)ggcoefplot(est, vcov = "hc1")
.
These on-the-fly adjustments are done via summary.fixest
, and so the effect is
just the same as passing an adjusted object directly, e.g.
ggcoefplot(summary(est, vcov = "hc1"))
. However, it may prove more convenient
for simultaneously adjusting a list of multiple models, e.g.
ggcoefplot(list(est1, est2, est3), vcov = "hc1")
. (#35)ggcoefplot
, a ggplot equivalent of coefplot
(#28).pt.size
argument for controlling the size of point markers (#27).
Thanks @jcvdav.keep
and drop
arguments for subsetting coefficients (#22).iplot()
(#e5cf0b0).log(y
(#20).marginaleffects::hypotheses()
internally for aggr_es()
to match
the upstream changes in marginaleffects.NEWS.md
file to track changes to the package.Any scripts or data that you put into this service are public.
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