-
Code improvements that made the package faster and more memory efficient
-
Improved automated testing and regression testing
-
Check if data is balanced if
panel = TRUE
andallow_unbalanced_panel = TRUE
. If it is, disableallow_unbalanced_panel
and proceed with panel data setup. This is different from the previous behavior, which would always proceed as ifpanel = FALSE
. -
Significantly reduced the number of recursive package dependencies, enabling faster installation times and a smaller build footprint.
-
Added wrapper function for HonestDiD package
-
Fix bug for setups where
gname
is not contained intname
(but is in thetname
range) -
Fix bug for including too many groups with universal base period in pre-treatment periods
-
Bug fix for anticipation using
notyettreated
comparison group
-
Bug fixes related unbalanced panel and clustered standard errors
-
Bug fixes for conditional_did_pretest
-
Even faster bootstrap code (thanks Kyle Butts)
-
Updated version requirement for
BMisc
package -
Bug fix for unbalanced panel and repeated cross sections in pre-treatment periods using universal base period
-
Code is substantially faster/more memory efficient
-
Support for universal base period
-
Major improvements to unit testing
-
Completely removed
mp.spatt
andmp.spatt.test
functions (which were the original names foratt_gt
) -
Simulation/testing code now exported
-
Removed some slow running checks
-
Multiplier bootstrap code is now written in C++
-
Improvements to error handling, added some additional warning messages, removed some unnecessary warning messages
-
Bug fixes for NA standard errors that occur with very small groups
-
Improved plots
-
Maximum event time for event studies
-
Compute critical value for simultaneous confidence bands even when some standard error is zero (set these to NA)
-
Improved codes for unbalanced panel data: faster and more memory efficient
-
Correct estimates of P(G=g|Eventually treated) with unbalanced panel data. This affects aggte objects with unbalanced panel data
-
Bug fixes for summary aggte objects
-
Allow clustering for unbalanced panel data
-
Fixed error in calendar-type aggregation within aggte function (point estimates were not being weighted by group-size; now they are).
-
Additional error handling
-
Big improvement on code base / functionality / testing
-
Deprecated mp.spatt function and replaced it with att_gt function
-
Calling att_gt is similar to calling mp.spatt; instead of formula for outcome of the form
y~treat
, now just pass the name of the outcome variable -
Deprecated mp.spatt function and replaced it with conditional_did_pretest function
-
New est_method parameter. Can call any function for 2x2 DID in the DRDID package (default is now doubly robust estimation, but inverse probability weights and regression estimators are also supported) as well as provide custom 2x2 DID estimators
-
Bug fixes for including groups that are already treated in the first period
-
Allow for user to select control group -- either never treated or not yet treated
-
Add functionality for uniform confidence bands for all aggregated treatment effect parameters
-
Introduced dynamic effects in pre-treatment periods. These allow for users to report event study plots that are common that include pre-treatment periods and are common in applied work. The event study plots in the did package are robust to selective treatment timing (unlike standard regression event study plots)
-
Support for using repeated cross sections data instead of panel data is much improved
-
Support for using sampling weights is much improved
-
Big improvement to website, vignettes, and code documentation
-
Code for dealing with unbalanced panels
-
Allow for event studies to be computed over subsets of event times
-
Allow for treatment anticipation via anticipation argument
- Corrected check problems
-
Improved ways to summarize aggregated treatment effect parameters
-
Fixed bug related to needing new version of BMisc
-
Fixed bug related to plotting with no pre-treatment periods
-
Improved ways to easily plot aggregated treatment effect parameters
-
Added some error handling for some cases with small group sizes, and fixed some cryptic error messages
-
Fixes handling for data being in format besides data.frame (e.g. tibble)
-
Add warnings about small group sizes which are a very common source of trouble
- Updates for handling repeated cross sections data, both estimation and inference
- bug fixes for testing without covariates, allowed to pass NULL in addition to ~1
-
fixed issues between BMisc and formula.tools
-
added point estimates for repeated cross sections data
- bug fixes for the case without any covariates
- first version of package, functions for computing group-time average treatment effects, combining them into a smaller number of parameters, and pre-testing the common trends assumption