The RItools
package implements useful functions for implementing randomization inference based statistical tests. The package provides tools for testing balance of observed covariates in observational studies using the methodology of:
Ben B. Hansen and Jake Bowers (2008). Covariate balance in simple,
stratified and clustered comparative studies. Statistical Science.
23(2):219--236.
See the online documentation for xbalance
for more details.
The package also provides outcome analysis of simple or block randomized trials (or matched observational studies) based on user defined models and test statistics. See the online documentation of parameterizedRandomizationDistribution
for more details.
RItools
is available on CRAN:
> install.packages("RItools")
> library("RItools")
These directions will install development version in a way that will not overwrite an existing installation of RItools
from CRAN. You will will need to know the name of the branch you wish to install.
master
: The current released version of RItools
and a holding place for small bug changes.randomization-distribution
: Experimental work on outcome analysis using user defined models of effects and test statistics. This branch contains the tools necessary to compute estimated treatment effects, p-values, and confidence intervals (regions) using direct simulation from the randomization distribution implied by the design of the experiment (or using the exact randomization distribution if the number of possible ways for the treatment to be assigned is relatively small).Install and load the devtools
package:
> install.packages("devtools")
> library("devtools")
Next, pick a location to install the package. For example, create a directory called ~/R/RItools.experimental/
(~
is short for my home directory on a UNIX system). For this session, we will set the library path to look in this location first and install the package there:
> .libPaths("~/R/RItools.experimental/") # <- your path here
> install_github("markmfredrickson/RItools")
The function install_github
will load the package automatically. To install from a branch of the repository, e.g. the randomization-distribution branch, instead use
> install_github("markmfredrickson/RItools@randomization-distribution")
In the future, if you wish load the downloaded version of RItools
in a new R
session you can use this one-liner:
> library("RItools", lib.loc = "~/R/RItools.experimental") # <- your path here