`clarify` 0.2.1

In sim_ame() and sim_adrf(), unit-level weights are no longer used to compute means, consistent with advice in Gabriel et al. (2023). For those using these functions after matching or weighting for the ATT or ATC, this will not change results. For matching or weighting for the ATE, this improves robustness against misspecified weights.
In sim_ame(), more than one variable can be supplied to var to generate average adjusted predictions or compute average marginal effects with other variables set to supplied values. The help page for sim_ame() has been retooled to reflect this.
In transform(), values can now be indicated by positional shortcuts of the form .b{#}, e.g., .b1 - .b2, to facilitate specifying transformations of the desired quantities without using the names of the quantities, which can be frustrating to use.
When reference = TRUE with plot(), a blue line at the median of the simulated estimates is also included on the plot; when this value does not align with the estimate, quantile confidence intervals may be invalid.

`clarify` 0.2.0

sim_ame() and sim_adrf() now have a by argument, which can be used to estimate quantities of interest within subsets of one or more variables.
sim_setx() can now receive a data frame for its x and x1 arguments.
sim_ame() can accept new options for contrast: "sr" for the survival ratio and "srr" for the switch relative risk.
Slight speed improvements in sim_ame() with continuous var and sim_adrf() with contrast =“amef”`.
Typo fixes in vignettes.

Documentation updates incorporating the work of Rainey (2023). clarify already implemented the recommendations in Rainey (2023) so no functionality has changed.

Added the argument reference to plot.clarify_est(), which adds a reference normal distribution to the density of the estimates.
Fixed error in sim() documentation about how degrees of freedom are computed. Thanks to @wviechtb. (#8)
Fixed a warning that can occur about recovering model data, from insight.

In summary.clarify_est(), null can now be supplied as a named vector to specify the quantities for which p-values should be computed.
Fixes in anticipation of breaking changes from marginaleffects to ensure compatibility (including with older versions).
Updates to the README and vignettes.