Package: factorEx 1.1.0
factorEx: Design and Analysis for Factorial Experiments
Provides design-based and model-based estimators for the population average marginal component effects in general factorial experiments, including conjoint analysis. The package also implements a series of recommendations offered in de la Cuesta, Egami, and Imai (2022) <doi:10.1017/pan.2020.40>, and Egami and Imai (2019) <doi:10.1080/01621459.2018.1476246>.
Authors:
factorEx_1.1.0.tar.gz
factorEx_1.1.0.zip(r-4.7)factorEx_1.1.0.zip(r-4.6)factorEx_1.1.0.zip(r-4.5)
factorEx_1.1.0.tgz(r-4.6-any)factorEx_1.1.0.tgz(r-4.5-any)
factorEx_1.1.0.tar.gz(r-4.7-any)factorEx_1.1.0.tar.gz(r-4.6-any)
factorEx_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
factorEx/json (API)
| # Install 'factorEx' in R: |
| install.packages('factorEx', repos = c('https://naoki-egami.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/naoki-egami/factorex/issues
- OnoBurden - Dataset from Ono and Burden
Last updated from:a5d4d56405. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 177 | ||
| source / vignettes | OK | 178 | ||
| linux-release-x86_64 | OK | 203 | ||
| macos-release-arm64 | OK | 122 | ||
| macos-oldrel-arm64 | OK | 117 | ||
| windows-devel | OK | 116 | ||
| windows-release | OK | 121 | ||
| windows-oldrel | OK | 105 | ||
| wasm-release | OK | 117 |
Exports:decompose_pAMCEdesign_pAMCEdiagnose_pAMCEmodel_pAMCEplot_decomposeplot_diagnoseweights_pAMCE
Dependencies:abindarmbootclicodacodetoolscpp11data.tablediagramdigestdoParallelestimatrfarverforeachFormulafuturefuture.applygenericsgenlassoggplot2globalsgluegtableigraphisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlme4magrittrMASSMatrixminqamvtnormnlmenloptrnumDerivparallellypbapplypbmcapplypkgconfigprodlimprogressrR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangS7sandwichscalesshapeSQUAREMstringistringrsurvivalvctrsviridisLitewithrzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Decompose the difference between the pAMCEs | decompose_pAMCE |
| Estimating the population AMCE using a design-based approach | design_pAMCE |
| Diagnose modeling assumptions for the model-based approach | diagnose_pAMCE |
| Estimating the population AMCE using a model-based approach | model_pAMCE |
| Dataset from Ono and Burden (2018) | OnoBurden |
| Plot decomposition of the difference between pAMCEs | plot_decompose |
| Plotting diagnostic checks | plot_diagnose |
| Plotting the estimated population AMCEs | plot.pAMCE |
| Summarizing the estimated population AMCEs | summary.pAMCE |
| Computing weights for estimating the population AMCE using a design-based approach | weights_pAMCE |
