SWSamp is a general purpose package to provide a suite of functions for the sample size calculations and power analysis in a Stepped Wedge Trial. Contains functions for closed-form sample size calculation (based on a set of specific models) and simulation-based procedures that can extend the basic framework.
There are two ways of installing
SWSamp. A "stable" version is packaged and binary files are available for Windows and as source. To install the stable version on a Windows machine, run the following commands
install.packages("SWSamp", repos=c("http://www.statistica.it/gianluca/R", "https://cran.rstudio.org", "https://www.math.ntnu.no/inla/R/stable"), dependencies=TRUE )
Note that you need to specify a vector of repositories - the first one hosts
SWSamp, while the second one should be an official CRAN mirror. You can select whichever one you like, but a CRAN mirror must be provided, so that
install.packages() can also install the "dependencies" (e.g. other packages that are required for
SWSamp to work). The third one is used to install the package
INLA, which can be used to perform simulation-based sample size calculations using a Bayesian approach. This process can be quite lengthy, if you miss many of the relevant packages.
To install from source (e.g. on a Linux machine), run
install.packages("SWSamp", repos=c("http://www.statistica.it/gianluca/R", "https://cran.rstudio.org", "https://www.math.ntnu.no/inla/R/stable"), type="source", dependencies=TRUE
The second way involves using the "development" version of
SWSamp - this will usually be updated more frequently and may be continuously tested. On Windows machines, you need to install a few dependencies, including Rtools first, e.g. by running
pkgs <- c("foreach", "doParallel", "iterators", "parallel", "Matrix","lme4","INLA","Rtools","devtools") repos <- c("https://cran.rstudio.com", "https://www.math.ntnu.no/inla/R/stable") install.packages(pkgs,repos=repos,dependencies = "Depends")
before installing the package using
Under Linux or MacOS, it is sufficient to install the package via
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.