swCRTdesign-package: Stepped Wedge Cluster Randomized Trial (SW CRT) Design

swCRTdesign-packageR 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.