quickmatch v0.2.1
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Quick Generalized Full Matching
Provides functions for constructing near-optimal generalized full matching.
Generalized full matching is an extension of the original full matching method
to situations with more intricate study designs. The package is made with
large data sets in mind and derives matches more than an order of magnitude
quicker than other methods.
Readme
quickmatch
quickmatch
provides functions for constructing near-optimal generalized full matchings. Generalized full matching is an extension of the original full matching method to situations with more intricate study designs. The package is made with large data sets in mind and derives matchings more than an order of magnitude quicker than other methods.
How to install
quickmatch
is on CRAN and can be installed by running:
install.packages("quickmatch")
How to install development version
It is recommended to use the stable CRAN version, but the latest development version can be installed directly from Github using devtools:
if (!require("devtools")) install.packages("devtools")
devtools::install_github("fsavje/quickmatch")
The package contains compiled code, and you must have a development environment to install the development version. (Use devtools::has_devel()
to check whether you do.) If no development environment exists, Windows users download and install Rtools and macOS users download and install Xcode.
Example on how to use quickmatch
# Load package
library("quickmatch")
# Construct example data
my_data <- data.frame(y = rnorm(100),
x1 = runif(100),
x2 = runif(100),
treatment = factor(sample(rep(c("T", "C"), c(25, 75)))))
# Make distances
my_distances <- distances(my_data, dist_variables = c("x1", "x2"))
### Average treatment effect (ATE)
# Make matching
my_matching_ate <- quickmatch(my_distances, my_data$treatment)
# Covariate balance
covariate_balance(my_data$treatment, my_data[c("x1", "x2")], my_matching_ate)
# Estimate effect
lm_match(my_data$y, my_data$treatment, my_matching_ate)
### Average treatment effect of the treated (ATT)
# Make matching
my_matching_att <- quickmatch(my_distances, my_data$treatment, target = "T")
# Covariate balance
covariate_balance(my_data$treatment, my_data[c("x1", "x2")], my_matching_att, target = "T")
# Estimate effect
lm_match(my_data$y, my_data$treatment, my_matching_att, target = "T")
Functions in quickmatch
Name | Description | |
covariate_balance | Covariate balance in matched sample | |
quickmatch-package | quickmatch: Quick Generalized Full Matching | |
is.qm_matching | Check qm_matching object | |
covariate_averages | Covariate averages in matched sample | |
quickmatch | Derive generalized full matchings | |
lm_match | Regression-based matching estimator of treatment effects | |
matching_weights | Unit weights implied by matching | |
qm_matching | Constructor for qm_matching objects | |
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Details
Type | Package |
Date | 2018-08-24 |
NeedsCompilation | yes |
License | GPL (>= 3) |
URL | https://github.com/fsavje/quickmatch |
BugReports | https://github.com/fsavje/quickmatch/issues |
Encoding | UTF-8 |
RoxygenNote | 6.1.0 |
Packaged | 2018-08-24 19:11:29 UTC; fredrik |
Repository | CRAN |
Date/Publication | 2018-08-24 21:00:02 UTC |
depends | distances , R (>= 3.4.0) |
imports | sandwich , scclust (>= 0.2.0) , stats |
suggests | testthat |
Contributors | Jasjeet Sekhon, Michael Higgins |
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