NEWS

---

fastdid 1.0.2 (2024-10-28)

fastdid 1.0.1

fastdid 1.0.0

• Release to CRAN!

fastdid 0.9.9

• add double did (see the vignette for the introduction)
• add parallel, parallization for unix systems, useful if the number of g-t is large.
• add full, return full result such as influence function, aggregate scheme, and such
• add min/max_dynamic, custom_scheme to experimental features

0.9.9.1 (2024/9/13): fix a bug that affects not-yet control with max treated group != max time

fastdid 0.9.4

Some BREAKING change is introduced in this update.

• add uniform confidence interval option with cband and significance level alpha, confidence interval are now provided in result as column att_ciub and att_cilb
• BREAKING: filtervar, max_control_cohort_diff, min_control_cohort_diff are moved into the experimental features. See the above section for the explanation.
• add max_dynamic and min_dynamic as experimental features.
• more informative error message when estimation fails for a specific gt, some internal interface overhaul

fastdid 0.9.3

• add anticipation and varying base period option
• add min and max control cohort difference
• add time-varying control (reference)
• add filtervar

0.9.3.1 (2024/5/24): fix the bug with univar == clustervar (TODO: address problems with name-changing and collision). 0.9.3.2 (2024/7/17): fix group_time result when using control_type = "notyet" and make the base period in plots adapt to anticipation. 0.9.3.3 (2024/7/22): fix anticipation out of bound problem, more permanent solution for group_time target problem

fastdid 0.9.2

• add support to doubly robust and outcome regression estimators
• add support to unbalanced panels (simple and ipw only)
• add support to balanced composition option in dynamics aggregation
• fixed argument checking that was not working properly
• set the default to copying the entire dataset to avoid unexpected modification of the original data (thanks @grantmcdermott for the suggestion.)

fastdid 0.9.1

• now supprts estimation for multiple outcomes in one go!
• data validation: no longer check missing values for columns not used.