Package: medflex 0.6-10

medflex: Flexible Mediation Analysis Using Natural Effect Models

Run flexible mediation analyses using natural effect models as described in Lange, Vansteelandt and Bekaert (2012) <doi:10.1093/aje/kwr525>, Vansteelandt, Bekaert and Lange (2012) <doi:10.1515/2161-962X.1014> and Loeys, Moerkerke, De Smet, Buysse, Steen and Vansteelandt (2013) <doi:10.1080/00273171.2013.832132>.

Authors:Johan Steen [aut, cre], Tom Loeys [aut], Beatrijs Moerkerke [aut], Stijn Vansteelandt [aut], Joris Meys [ctb], Theis Lange [ctb], Joscha Legewie [ctb], Paul Fink [ctb], Sanford Weisberg [ctb], Yves Rosseel [ctb]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
medflex/json (API)

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

Bug tracker:https://github.com/jmpsteen/medflex/issues

Datasets:

On CRAN:

Conda:

causal-inferenceflexible-modelingmediation-analysis

7.38 score 25 stars 95 scripts 991 downloads 19 mentions 6 exports 73 dependencies

Last updated from:327ff7a3fc. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE176
source / vignettesOK235
linux-release-x86_64NOTE143
macos-release-arm64NOTE165
macos-oldrel-arm64NOTE146
windows-develNOTE93
windows-releaseNOTE107
windows-oldrelNOTE95
wasm-releaseOK166

Exports:neEffdecompneImputeneLhtneModelneWeightplot.neLht

Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrmultcompmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7sandwichscalesSparseMstringistringrsurvivalTH.datatibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

Flexible mediation analysis in R using natural effect models
Introduction | The mediation formula | Mediation analysis via natural effect models | Dealing with different types of variables | Effect modification of natural effects | Tools for calculating and visualizing causal effect estimates | Population-average natural effects | Intermediate confounding: A joint mediation approach | Weighting or imputing? | Concluding remarks | ​
Rendered frommedflex.Rnwusingutils::Sweave

Last update: 2021-02-23
Started: 2015-02-04

Sandwich estimator derivations for natural effect model parameters
Rendered fromsandwich.Rnwusingutils::Sweave

Last update: 2015-09-13
Started: 2015-02-04

Readme and manuals

Help Manual

Help pageTopics
Expanded datasetexpData
Methods for expanded datasetsexpData-methods residualPlot.expData residualPlots.expData residuals.expData weights.expData
Expand the dataset and impute nested counterfactual outcomesneImpute
Expand the dataset and impute nested counterfactual outcomesneImpute.default
Expand the dataset and impute nested counterfactual outcomesneImpute.formula
Linear hypotheses for natural effect modelsneEffdecomp neEffdecomp.neModel neLht neLht.neModel
Methods for linear hypotheses in natural effect modelsconfint.neLht confint.neLhtBoot neLht-methods summary.neLht
Fit a natural effect modelneModel
Methods for natural effect modelscoef.neModel confint.neModel confint.neModelBoot neModel-methods residualPlot.neModel residualPlots.neModel summary.neModel vcov.neModel weights.neModel
Expand the dataset and calculate ratio-of-mediator probability weightsneWeight
Expand the dataset and calculate ratio-of-mediator probability weightsneWeight.default
Expand the dataset and calculate ratio-of-mediator probability weightsneWeight.formula
Confidence interval plots for linear hypotheses in natural effect modelsplot.neEffdecomp plot.neLht plot.neLhtBoot
Confidence interval plots for natural effect componentsplot.neModel plot.neModelBoot
UPB dataUPBdata