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SteppedPower - Power Calculation for Stepped Wedge Designs

SteppedPower offers tools for power and sample size calculation as well as design diagnostics for longitudinal mixed model settings, with a focus on stepped wedge designs. All calculations are oracle estimates i.e. assume random effect variances to be known (or guessed) in advance.

Installation

Install from CRAN with install.packages("SteppedPower"). Current version on CRAN is 0.3.1.

To install the latest stable version type
devtools::install_github("PMildenb/SteppedPower", build_vignettes=TRUE)

The development version with the most recent changes can be installed with devtools::install_github("PMildenb/SteppedPower", ref='devel', build_vignettes=TRUE)

Vignette

The vignette can be viewed with vignette("Getting_Started", package="SteppedPower")

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Version

Install

install.packages('SteppedPower')

Monthly Downloads

622

Version

0.3.1

License

MIT + file LICENSE

Maintainer

Philipp Mildenberger

Last Published

December 16th, 2021

Functions in SteppedPower (0.3.1)

compute_wlsPower

Compute power via weighted least squares
SteppedPower-pkg

SteppedPower
VarClosed_Li

Closed formula for treatment variance, with proportional decay
construct_CovMat

Construct a Covariance Matrix
VarClosed_Kasza

Closed formula for treatment variance in open cohort settings
alpha012_to_RandEff

Correlation structure: transform alpha to random effects
construct_CovBlk

Construct a Single Block of the Covariance Matrix
RandEff_to_alpha012

Correlation structure: transform random effects to alpha
plot_CovMat

Visualise a Covariance Matrix
plot_InfoContent

plot the information content of a wls object
plot.wlsPower

plot an object of class `wlsPower`
construct_trtMat

Construct Treatment Matrix
construct_DesMat

Construct the Design Matrix
construct_CovSubMat

Construct a Block of the Covariance Matrix
construct_incompMat

Constructs a matrix of 0 and 1 for unobserved and observed cluster periods, respectively.
construct_timeAdjust

Construct the time period adjustment in the design matrix
plot_CellWeights

plot cell contributions (weights) of a wls object
tTestPwr

Compute Power of a Wald Test
wlsPower

Compute power via weighted least squares
print.DesMat

print.DesMat
print.wlsPower

Print an object of class `wlsPower`
plot.DesMat

plot.DesMat