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TsaiLintung committed Sep 8, 2024
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4 changes: 0 additions & 4 deletions .github/workflows/test-coverage.yaml
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name: Run tests and upload coverage

on:
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pull_request:
branches: [main, master]

jobs:
test:
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9 changes: 4 additions & 5 deletions README.md
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<!-- badges: start -->
[![R-CMD-check](https://github.com/TsaiLintung/fastdid/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/TsaiLintung/fastdid/actions/workflows/R-CMD-check.yaml)
[![codecov](https://codecov.io/github/TsaiLintung/fastdid/graph/badge.svg?token=0EYF1DIBRF)](https://codecov.io/github/TsaiLintung/fastdid)
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fastdid implements the Difference-in-Differences (DiD) estimators in [Callaway and Sant'Anna's (2021)](https://www.sciencedirect.com/science/article/pii/S0304407620303948), it is

- fast, reducing the computation time with millions of units from hours to [seconds](articles/misc.html),
- fast, reducing the computation time with millions of units from hours to [seconds](https://tsailintung.github.io/fastdid/articles/misc.html#performance),
- flexible, with extensions such as [time-varying covariates](https://arxiv.org/abs/2406.15288) and [multiple events](not_ready_yet) (coming soon!).

# Getting Started
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# More

- [did](https://bcallaway11.github.io/did/articles/did-basics.html): staggered Difference in Difference by Callaway and Sant'Anna
- [fastdid](../reference/fastdid.html): full list of arguments and features.
- [double](articles/double.html): introduction to DiD with multiple events.
- [misc](articles/misc.html): comparison with [did](https://github.com/bcallaway11/did), benchmark, tests, and experimental features.
- [fastdid](https://tsailintung.github.io/fastdid/reference/fastdid.html): full list of arguments and features.
- [double](https://tsailintung.github.io/fastdid/articles/double.html): introduction to DiD with multiple events.
- [misc](https://tsailintung.github.io/fastdid/articles/misc.html): comparison with [did](https://github.com/bcallaway11/did), benchmark, tests, and experimental features.

# Acknowledgments

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articles:
double: double.html
misc: misc.html
last_built: 2024-08-25T23:56Z
last_built: 2024-09-08T19:08Z
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reference: https://tsailintung.github.io/fastdid/reference
article: https://tsailintung.github.io/fastdid/articles
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4 changes: 2 additions & 2 deletions vignettes/misc.Rmd
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## Basics: comparison with `did`

For features included in CS, `fastdid` maintains a maximum of 1% difference from results from the `did` package. This margin of error is mostly for bootstrapped results due to its inherent randomess. For point estimates, the difference is smaller than 1e-12, and is most likely the result of [floating-point error](https://en.wikipedia.org/wiki/Floating-point_error_mitigation). The relevant test files are [group-time](https://github.com/TsaiLintung/fastdid/blob/main/inst/tinytest/test_2_compare_gt.R) and [aggregates](https://github.com/TsaiLintung/fastdid/blob/main/inst/tinytest/test_3_compare_agg.R).
For features included in CS, `fastdid` maintains a maximum of 1% difference from results from the `did` package. This margin of error is mostly for bootstrapped results due to its inherent randomess. For point estimates, the difference is smaller than 1e-12, and is most likely the result of [floating-point error](https://en.wikipedia.org/wiki/Floating-point_error_mitigation). The relevant test files are [compare_est.R](https://github.com/TsaiLintung/fastdid/blob/main/inst/tinytest/test_2_compare_est.R).

## Extensions: coverage test

For features not included in CS, `fastdid` maintains that the 95% confidence intervals have a coverage rate between 94% and 96%.

The coverage rate is calculated by running 200 iterations. In each iteration, we test whether the confidence interval estimated covers the group-truth values. We then average the rate across iterations. Due to the randomness of coverage, the realized coverage fall outside of the thresholds in about 1% of the time. The relevant test file is [coverage](https://github.com/TsaiLintung/fastdid/blob/main/inst/tinytest/test_5_coverage.R).
The coverage rate is calculated by running 200 iterations. In each iteration, we test whether the confidence interval estimated covers the group-truth values. We then average the rate across iterations. Due to the randomness of coverage, the realized coverage fall outside of the thresholds in about 1% of the time. The relevant test file is [coverage.R](https://github.com/TsaiLintung/fastdid/blob/main/inst/tinytest/test_99_coverage.R).

## Experimental Features: not tested

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