Package: simr 1.0.9-1

simr: Power Analysis for Generalised Linear Mixed Models by Simulation

Calculate power for generalised linear mixed models, using simulation. Designed to work with models fit using the 'lme4' package. Described in Green and MacLeod, 2016 <doi:10.1111/2041-210X.12504>.

Authors:Peter Green [aut, cre], Catriona MacLeod [aut], Phillip Alday [ctb]

simr_1.0.9-1.tar.gz
simr_1.0.9-1.zip(r-4.7)simr_1.0.9-1.zip(r-4.6)simr_1.0.9-1.zip(r-4.5)
simr_1.0.9-1.tgz(r-4.6-any)simr_1.0.9-1.tgz(r-4.5-any)
simr_1.0.9-1.tar.gz(r-4.7-any)simr_1.0.9-1.tar.gz(r-4.6-any)
simr_1.0.9-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
simr/json (API)

# Install 'simr' in R:
install.packages('simr', repos = c('https://pitakakariki.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pitakakariki/simr/issues

Datasets:

On CRAN:

Conda:

11.16 score 77 stars 1 packages 1.0k scripts 3.9k downloads 46 mentions 23 exports 74 dependencies

Last updated from:33ee7dfa8c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK195
source / vignettesOK209
linux-release-x86_64OK188
macos-release-arm64OK165
macos-oldrel-arm64OK253
windows-develOK126
windows-releaseOK137
windows-oldrelOK125
wasm-releaseOK153

Exports:coef<-comparedoFitdoSimdoTestextendfcomparefixedfixef<-getDatagetData<-getSimrOptionlastResultmakeGlmermakeLmerpowerCurvepowerSimrandomrcomparescale<-sigma<-simrOptionsVarCorr<-

Dependencies:abindbackportsbinombootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclelme4lmerTestlmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplotrixplyrpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangRLRsimS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

Power analysis from scratch
Covariates and parameters | Build a model object | Start the power analysis
Rendered fromfromscratch.Rmdusingknitr::rmarkdown

Last update: 2018-04-02
Started: 2015-07-05

Test examples
Binomial GLMM with a categorical predictor | Models with interaction or quadratic terms | Cake | Budworms | Single random effects | Multiple random effects | A note about errors during simulation
Rendered fromexamples.Rmdusingknitr::rmarkdown

Last update: 2015-12-14
Started: 2015-01-27

Readme and manuals

Help Manual

Help pageTopics
simr: Simulation-based power calculations for mixed models.simr-package simr
Fit model to a new response.doFit
Generate simulated response variables.doSim
Apply a hypothesis test to a fitted model.doTest
Extend a longitudinal model.extend
Get an object's data.getData getData<-
Recover an unsaved simulationlastResult
Create an artificial mixed model objectmakeGlmer makeLmer
Modifying model parameters.coef<- fixef<- modify scale<- sigma<- VarCorr<-
Estimate power at a range of sample sizes.powerCurve
Estimate power by simulation.powerSim
Report simulation resultsconfint.powerCurve confint.powerSim print.powerCurve print.powerSim summary.powerCurve summary.powerSim
Example dataset.simdata
Options Settings for 'simr'getSimrOption simrOptions
Specify a statistical test to applycompare fcompare fixed random rcompare tests