emfx(..., predict = c("response", "link")), where the latter
allows for obtaining the linear prediction for non-linear models. Internally
passed as marginaleffects::slopes(..., type = predict), thus avoiding a clash
with the topline emfx(..., type = <aggregration_type>) argument. (#49)cgroup = "never) due
to incorrect subsetting prior to recovering the marginal effects. Thanks to
@paulofelipe for reporting (#37).Fixed internal centering procedure and handling of multiple covariate levels
(#30, #31). These fixes should have no impact on the main ATT estimates (i.e.,
typical use of the package). But it may lead to differences in the heterogeneous
ATTs---i.e., via the xvar arg---which were incorrectly estimated in some
cases. Thanks to @PhilipCarthy for flagging and to @frederickluser for helpful
discussions
Fixed internal and upstream bug which was causing model offsets to error (#28, thanks @mariofiorini for the initial report and several others for helpful discussion). Note that this fix requires insight >= 0.19.1.8, which is the development version at the time of writing. More information available here: https://github.com/easystats/insight/pull/759
emfx().\dontrun to avoid triggering CRAN NOTEs on
Windows for exceeding 5 seconds execution time. Note that the package homepage
still runs these Examples if users want to inspect the output online.Support for estimating heterogeneous treatment effects via the new
etwfe(..., xvar = <xvar> argument (#16, thanks to @frederickluser).
Automatically extends to emfx() via the latter's by_xvar argument (#21).
More details are provided in the dedicated "Heterogeneous treatment effects"
section of the vignette and help documentation
The new emfx(..., collapse = TRUE) argument can substantially reduce
estimation times for large datasets (#19, thanks @frederickluser). This
performance boost does trade off against a loss in estimate accuracy. But
testing suggests that the difference is relatively minor for typical use cases
(i.e., results are equivalent up to the 1st or 2nd significant decimal place,
and sometimes even better). Please let us know if you find edge cases where this
is not true. More details are available in the dedicated "Performance tips"
section of the vignette and help documentation, including advice for combining
collapsing with emfx(..., vcov = FALSE) (which yields an even more dramatic
speed boost but at a cost of not reporting any standard errors).
Users can now use a 1 on the fml RHS to indicate that there are no control variables
as part of the etwfe call, e.g. etwfe(y ~ 1, ...). This provides a second
way of indicating no controls, alongside the existing 0 option, e.g. etwfe(y ~ 0, ...)
summary() on emfx objects for pretty printing, and that the (former) "dydx"
column of the resulting object is now named "estimate". These changes are
reflected in the updated documentation.Various documentation improvements. For example, the aforementioned sections on Heterogeneous TEs and Performance tips. I have also removed some warnings about the use of time-varying controls (#17). In truth, I can't quite recall why I included these warnings in the first place and testing confirms that it does not appear to pose a problem for the ETWFE framework. Thanks to Felix Pretis for prompting me to revisit this implicit restriction, including forwarding some relevant correspondence with Prof. Wooldridge.
data.table is added to Imports and thus becomes a direct dependency. It was already an indirect dependency through marginaleffects.
It's now possible to install the development version of the package from R-universe. Details are provided in the README.
The .Dtreat indicator variable created during the etwfe call is now
logical instead of integer (#14). This fix yields slightly different effect
sizes for emfx output when applied to non-linear model families (e.g.,
etwfe(..., family = "poisson"). The reason is that we are now implicitly
calling marginaleffects::comparisons under the hood rather than
marginaleffects::marginaleffects. Note that the main etwfe coefficients (for
any family) are unaffected, and the same is also true for emfx when applied to
a linear model (i.e., the default).
The (optional) ivar argument of etwfe() has been moved down the argument
order list from second position to fifth (i.e., after the data argument). This
means that the four required arguments of function now occupy the top positions,
which could enable shorter, unnamed notation like
etwfe(y ~ x, year, cohort, dat).
emfx now allows (time-invariant) interacted control variables on the fml RHS.
emfx now has a post_only logical argument, which may be useful for plotting
aesthetics (but not inference). See the example in the introductory vignette.
Various improvements to the documentation (restructuring, fixed typos, etc.)