Package: EquiTrends 1.0.0

Ties Bos

EquiTrends: Equivalence Testing for Pre-Trends in Difference-in-Differences Designs

Testing for parallel trends is crucial in the Difference-in-Differences framework. To this end, this package performs equivalence testing in the context of Difference-in-Differences estimation. It allows users to test if pre-treatment trends in the treated group are “equivalent” to those in the control group. Here, “equivalence” means that rejection of the null hypothesis implies that a function of the pre-treatment placebo effects (maximum absolute, average or root mean squared value) does not exceed a pre-specified threshold below which trend differences are considered negligible. The package is based on the theory developed in Dette & Schumann (2024) <doi:10.1080/07350015.2024.2308121>.

Authors:Ties Bos [aut, cre], Martin Schumann [ctb]

EquiTrends_1.0.0.tar.gz
EquiTrends_1.0.0.tar.gz(r-4.7-arm64)EquiTrends_1.0.0.tar.gz(r-4.7-x86_64)EquiTrends_1.0.0.tar.gz(r-4.6-arm64)EquiTrends_1.0.0.tar.gz(r-4.6-x86_64)
EquiTrends_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
EquiTrends/json (API)
NEWS

# Install 'EquiTrends' in R:
install.packages('EquiTrends', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tiesbos/equitrends/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

1.70 score 4 scripts 145 downloads 4 exports 36 dependencies

Last updated from:da1101b953. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK153
linux-devel-x86_64OK151
source / vignettesOK202
linux-release-arm64OK189
linux-release-x86_64OK153
wasm-releaseOK182

Exports:maxEquivTestmeanEquivTestrmsEquivTestsim_paneldata

Dependencies:bdsmatrixcliclubSandwichcollapsedigestdplyrFormulagenericsgluelatticelifecyclelmtestmagrittrMASSmaxLikmiscToolsnlmenloptrpillarpkgconfigplmR6rbibutilsRcppRcppArmadilloRcppParallelRdpackrlangsandwichtibbletidyselectutf8vctrsVGAMwithrzoo

Readme and manuals

Help Manual

Help pageTopics
Equivalence Testing for Pre-Trends in Difference-in-Differences DesignsEquiTrends-package EquiTrends
Finding the restricted placebo coefficients for the maximum equivalence test based on the bootstrap approachesboot_optimization_function
Data Construction Function for EquiTrendsEquiTrends_dataconstr
Input Checks Function for EquiTrendsEquiTrends_inputcheck
Equivalence Test for Pre-trends based on the Maximum Absolute Placebo CoefficientmaxEquivTest
Additional input checks for the maxEquivTest functionmaxTest_error
An internal function of the EquiTrends Maximum Equivalence Testing procedure using the Bootstrap approaches.maxTestBoot_func
An internal function of the EquiTrends Maximum Equivalence Testing procedure using the Intersection Union approach.maxTestIU_func
Finding the minimum equivalence threshold for the equivalence test based on the IU procedure for the maximum placebo coefficient.maxTestIU_optim_func
Equivalence Test for Pre-trends based on the Mean Placebo CoefficientmeanEquivTest
An internal function of the EquiTrends Mean Equivalence Testing proceduremeanTest_func
Finding the minimum equivalence threshold for the mean equivalence testmeanTest_optim_func
Print maxEquivTestBoot objectsprint.maxEquivTestBoot
Print maxEquivTestIU objectsprint.maxEquivTestIU
Print meanEquivTest objectsprint.meanEquivTest
Print rmsEquivTest objectsprint.rmsEquivTest
Equivalence Test for Pre-trends based on the RMS Placebo CoefficientrmsEquivTest
Additional input checks for the rmsEquivTest functionrmsTest_error
An internal function of the RMS Equivalence Testing procedurermsTest_func
Calculating the constrained variance of the residuals for the Boostrap approaches in the EquiTrends Maximum Equivalence Testing procedure, according to Dette & Schumann (2024).sigma_hathat_c
Checking input for the sim_paneldata functionsim_check
Simulating a panel data for a binary treatmentsim_paneldata
Calculating the critical value for the W distribution as construced in Dette & Schumann (2024).W_critical_value