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Improve code to avoid redundant data checks
Use fastglm instead of parglm for improved speed
Restore solve as default to invert matrix, as it is faster than qr.solve for small matrices.
Improve error handling for non-invertible matrices.
Changing estimation methods for fastglm and parglm (in place of lm and glm).
Do not let the estimated propensity score be above 1 - 1e-6 (instead of 1 - e-16).
Speed up data processing using Rcpp
The weights are now enforced to be normalized and have mean 1 across all observations.
Use qr.solve as default (instead of solve)
Drop collinear variables in pre_process_drdid.R (useful in drdid command but not other commands)
Add compatibility with R 3.5
Improve invertibility of outcome regression design matrix
Add new flags for non-unique unit identifier
Better handle of factor variables as covariates
Allows for treating covariates as factor and alike when computing DiD
Improve error and warning handling due to collinearity and convergence issues.
First official version of package, functions for computing a variety of difference-in-differences (DiD) estimators for the ATT.
Documentation is improved compared to the devel version, including examples for every function now.
Created wrapper function drdid, ordid
and ipwdid to implement doubly-robust, outcome regression
and inverse probability weighted DID estimators.
Add dataset used in the empirical application of Sant’Anna and Zhao (2020).
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They may not be fully stable and should be used with caution. We make no claims about them.
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