Heterogeneous Treatment Effects in Regression Analysis
c(
person("Tymon", "Sloczynski", role = c("aut"), email = "tslocz@brandeis.edu"),
person("Mark", "McAvoy", role = c("cre"), email = "mcavoy@brandeis.edu"))
Computes diagnostics for linear regression when treatment effects are heterogeneous.
The output of 'hettreatreg' represents ordinary least squares (OLS)
estimates of the effect of a binary treatment as a weighted average of the average treatment effect
on the treated (ATT) and the average treatment effect on the untreated (ATU).
The program estimates the OLS weights on these parameters, computes the associated model diagnostics,
and reports the implicit OLS estimate of the average treatment effect (ATE).
See Sloczynski (2019), <http://people.brandeis.edu/~tslocz/Sloczynski_paper_regression.pdf>.
Tymon Sloczynski [aut],
Mark McAvoy [cre]

Fisherian and Neymanian Methods for Detecting and Measuring
Treatment Effect Variation
c(
person("Peng", "Ding", email = "pengdingpku@berkeley.edu", role = "aut"),
person("Avi", "Feller", email = "afeller@berkeley.edu", role = "aut"),
person("Ben", "Fifield", email = "benfifield@gmail.com", role = c("aut", "cre")),
person("Luke", "Miratrix", email = "lmiratrix@g.harvard.edu", role = "aut")
)
Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <arXiv:1412.5000>,
and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <arXiv:1605.06566>
for testing whether there is unexplained variation in treatment effects across observations, and for characterizing
the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions
implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test.
quantreg, plyr, mvtnorm, MASS, foreach, parallel, doParallel,
moments, formula.tools, purrr, dplyr, tidyverse
Peng Ding [aut],
Avi Feller [aut],
Ben Fifield [aut, cre],
Luke Miratrix [aut]

Structural Handling of Finnish Personal Identity Numbers
c(
person("Pyry", "Kantanen", email = "pyry.kantanen@gmail.com", role = c("aut", "cre")),
person("Mans", "Magnusson", role = "aut"),
person("Jussi", "Paananen", role = "aut"),
person("Leo", "Lahti", role = "aut")
)
Structural handling of Finnish identity numbers (persons and companies); extract information, check ID validity and diagnostics.
Cairo, checkmate, lubridate, dplyr, knitr, testthat,
rmarkdown, covr
Pyry Kantanen [aut, cre],
Mans Magnusson [aut],
Jussi Paananen [aut],
Leo Lahti [aut]