swCRTdesign-package: Stepped Wedge Cluster Randomized Trial (SW CRT) Design
In swCRTdesign: Stepped Wedge Cluster Randomized Trial (SW CRT) Design
swCRTdesign-package R Documentation
Stepped Wedge Cluster Randomized Trial (SW CRT) Design
Description
This package includes functions for the design and analysis
of stepped wedge cluster randomized trials. For additional
guidance, see (Voldal EC, Hakhu NR, Xia F, Heagerty PJ,
Hughes JP. swCRTdesign: An R package for stepped wedge
trial design and analysis. Computer Methods and Programs
in Biomedicine 2020;196:105514. Nine primary functions
- swPwr, swSiz, swGlmPwr,
swGlmSiz, swSimPwr, swSim,
swSim2, swSummary, and swPlot -
and two support functions - blkDiag and swDsn
- are included.
The blkDiag function creates a
block diagonal matrix from a specified array or list of
block-matrices. The swDsn function creates a
stepped wedge (SW) design object based on specified
information on clusters, time points, and the arms of
the cluster randomized trial (CRT).
The swPwr
function computes the (two-sided) power of treatment
effect (\theta) for the specified SW CRT design
via weighted least squares (WLS), where the response/outcome
of interest is assumed to come from a mixed effects model
with normal or binomial errors, linear link and random
time effects and (possibly correlated) random intercepts
and random treatment effects. The random time effects
apply to all time points, and time is treated as categorical.
An exponentially decaying autocorrelation structure is also supported.
swSiz is a wrapper function for swPwr and
allows one to compute the cluster-period size for a given
design and power.
swGlmPwr has functionality similar to swPwr and
does power calculations
using the generalized linear mixed model framework
(Xia et al, 2019); swGlmSiz is the corresponding
wrapper function for computing cluster-period size.
swSimPwr simulates data and runs analyses using the
linear mixed model or generalized linear mixed model
framework to compute power via simulation. swPwr,
swSiz, swGlmPwr, swGlmSiz
and swSimPwr provide power/sample size
calculations for both an immediate treatment (IT) model
and an exposure time indicator (ETI) model (Kenny et al, 2022)
and can handle cross-sectional or closed cohort designs.
The swSim function generates individual-level data
consisting of response, treatment, time, time on treatment and
cluster id variables (and individual id for a closed cohort)
based on a specified SW CRT design. swSim2 extends the
functionality of swSim by allowing one to simulate data
with an exponentially decaying autocorrelation structure as
described in Kasza et al. (2019). In addition, swSim2 uses
the glmmTMB function simulate_new to simulate datasets.
swSim has been retained for backwards compatability.
The swSummary function computes the mean, sum, or
number of non-missing response values for clusters separately
or aggregated by wave at each time point from stepped wedge
data that includes, at least, response, treatment, time, and
cluster variables.
The swPlot function plots mean
response as a combined or separate plot, for waves and clusters.
Some features of the package are also available as a shiny app,
available online (https://swcrtdesign.shinyapps.io/stepped_wedge_power_calculation/)
or to download and run locally (https://github.com/swCRTdesign/Stepped-wedge-power-calculation).
Details
Package: swCRTdesign
Type: Package
Version: 4.1
Date: 2025-08-18
License: GPL (>= 2)
Author(s)
James P Hughes, Navneet R Hakhu, Emily C Voldal, and Fan Xia
Maintainer: James P Hughes <jphughes@uw.edu>
References
Hussey MA, Hughes JP. Design and analysis of stepped wedge cluster randomized trials. Contemporary Clinical Trials 2007;28:182-191.
Kenny A, Voldal E, Xia F, Heagerty PJ, Hughes JP. Analysis of stepped wedge cluster randomized trials in the presence of a time-varying treatment effect. Statistics in Medicine, in press, 2022.
Voldal EC, Hakhu NR, Xia F, Heagerty PJ, Hughes JP. swCRTdesign: An R package for stepped wedge trial design and analysis. Computer Methods and Programs in Biomedicine 2020;196:105514.
Xia F, Hughes JP, Voldal EC, Heagerty PJ. Power and sample size calculation for stepped-wedge designs with discrete outcomes. Trials. 2021 Dec;22(1):598.
swCRTdesign documentation built on Sept. 9, 2025, 5:55 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| swCRTdesign-package | R Documentation |
Stepped Wedge Cluster Randomized Trial (SW CRT) Design
Description
This package includes functions for the design and analysis
of stepped wedge cluster randomized trials. For additional
guidance, see (Voldal EC, Hakhu NR, Xia F, Heagerty PJ,
Hughes JP. swCRTdesign: An R package for stepped wedge
trial design and analysis. Computer Methods and Programs
in Biomedicine 2020;196:105514. Nine primary functions
- swPwr, swSiz, swGlmPwr,
swGlmSiz, swSimPwr, swSim,
swSim2, swSummary, and swPlot -
and two support functions - blkDiag and swDsn
- are included.
The blkDiag function creates a
block diagonal matrix from a specified array or list of
block-matrices. The swDsn function creates a
stepped wedge (SW) design object based on specified
information on clusters, time points, and the arms of
the cluster randomized trial (CRT).
The swPwr
function computes the (two-sided) power of treatment
effect (\theta) for the specified SW CRT design
via weighted least squares (WLS), where the response/outcome
of interest is assumed to come from a mixed effects model
with normal or binomial errors, linear link and random
time effects and (possibly correlated) random intercepts
and random treatment effects. The random time effects
apply to all time points, and time is treated as categorical.
An exponentially decaying autocorrelation structure is also supported.
swSiz is a wrapper function for swPwr and
allows one to compute the cluster-period size for a given
design and power.
swGlmPwr has functionality similar to swPwr and
does power calculations
using the generalized linear mixed model framework
(Xia et al, 2019); swGlmSiz is the corresponding
wrapper function for computing cluster-period size.
swSimPwr simulates data and runs analyses using the
linear mixed model or generalized linear mixed model
framework to compute power via simulation. swPwr,
swSiz, swGlmPwr, swGlmSiz
and swSimPwr provide power/sample size
calculations for both an immediate treatment (IT) model
and an exposure time indicator (ETI) model (Kenny et al, 2022)
and can handle cross-sectional or closed cohort designs.
The swSim function generates individual-level data
consisting of response, treatment, time, time on treatment and
cluster id variables (and individual id for a closed cohort)
based on a specified SW CRT design. swSim2 extends the
functionality of swSim by allowing one to simulate data
with an exponentially decaying autocorrelation structure as
described in Kasza et al. (2019). In addition, swSim2 uses
the glmmTMB function simulate_new to simulate datasets.
swSim has been retained for backwards compatability.
The swSummary function computes the mean, sum, or
number of non-missing response values for clusters separately
or aggregated by wave at each time point from stepped wedge
data that includes, at least, response, treatment, time, and
cluster variables.
The swPlot function plots mean
response as a combined or separate plot, for waves and clusters.
Some features of the package are also available as a shiny app, available online (https://swcrtdesign.shinyapps.io/stepped_wedge_power_calculation/) or to download and run locally (https://github.com/swCRTdesign/Stepped-wedge-power-calculation).
Details
| Package: | swCRTdesign |
| Type: | Package |
| Version: | 4.1 |
| Date: | 2025-08-18 |
| License: | GPL (>= 2) |
Author(s)
James P Hughes, Navneet R Hakhu, Emily C Voldal, and Fan Xia
Maintainer: James P Hughes <jphughes@uw.edu>
References
Hussey MA, Hughes JP. Design and analysis of stepped wedge cluster randomized trials. Contemporary Clinical Trials 2007;28:182-191.
Kenny A, Voldal E, Xia F, Heagerty PJ, Hughes JP. Analysis of stepped wedge cluster randomized trials in the presence of a time-varying treatment effect. Statistics in Medicine, in press, 2022.
Voldal EC, Hakhu NR, Xia F, Heagerty PJ, Hughes JP. swCRTdesign: An R package for stepped wedge trial design and analysis. Computer Methods and Programs in Biomedicine 2020;196:105514.
Xia F, Hughes JP, Voldal EC, Heagerty PJ. Power and sample size calculation for stepped-wedge designs with discrete outcomes. Trials. 2021 Dec;22(1):598.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.