Package: mlpwr 1.1.1.9000
mlpwr: A Power Analysis Toolbox to Find Cost-Efficient Study Designs
We implement a surrogate modeling algorithm to guide simulation-based sample size planning. The method is described in detail in our paper (Zimmer & Debelak (2023) <doi:10.1037/met0000611>). It supports multiple study design parameters and optimization with respect to a cost function. It can find optimal designs that correspond to a desired statistical power or that fulfill a cost constraint. We also provide a tutorial paper (Zimmer et al. (2023) <doi:10.3758/s13428-023-02269-0>).
Authors:
mlpwr_1.1.1.9000.tar.gz
mlpwr_1.1.1.9000.zip(r-4.5)mlpwr_1.1.1.9000.zip(r-4.4)mlpwr_1.1.1.9000.zip(r-4.3)
mlpwr_1.1.1.9000.tgz(r-4.5-any)mlpwr_1.1.1.9000.tgz(r-4.4-any)mlpwr_1.1.1.9000.tgz(r-4.3-any)
mlpwr_1.1.1.9000.tar.gz(r-4.5-noble)mlpwr_1.1.1.9000.tar.gz(r-4.4-noble)
mlpwr_1.1.1.9000.tgz(r-4.4-emscripten)mlpwr_1.1.1.9000.tgz(r-4.3-emscripten)
mlpwr.pdf |mlpwr.html✨
mlpwr/json (API)
NEWS
| # Install 'mlpwr' in R: |
| install.packages('mlpwr', repos = c('https://flxzimmer.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/flxzimmer/mlpwr/issues
- extensions_results - Results of the extensions vignette
Last updated 6 months agofrom:133bfe8a91. Checks:6 OK, 3 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Apr 02 2025 |
| R-4.5-win | NOTE | Apr 02 2025 |
| R-4.5-mac | NOTE | Apr 02 2025 |
| R-4.5-linux | NOTE | Apr 02 2025 |
| R-4.4-win | OK | Apr 02 2025 |
| R-4.4-mac | OK | Apr 02 2025 |
| R-4.4-linux | OK | Apr 02 2025 |
| R-4.3-win | OK | Apr 02 2025 |
| R-4.3-mac | OK | Apr 02 2025 |
Exports:example.simfunfind.designsimulations_data
Dependencies:clicolorspacedata.tableDiceKrigingdigestfansifarverggplot2gluegtableisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6randtoolboxRColorBrewerrgenoudrlangrlistrngWELLscalestibbleutf8vctrsviridisLitewithrXMLyaml
ANOVA Application
Rendered fromANOVA_Vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2024-10-04
Started: 2023-09-08
Extensions
Rendered fromextensions.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2023-08-07
Started: 2023-01-07
GLM Application
Rendered fromGLM_Vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2024-10-04
Started: 2023-09-08
IRT Application
Rendered fromIRT_Vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2024-10-04
Started: 2023-09-08
Multilevel Application
Rendered fromMLM_Vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2024-10-04
Started: 2023-09-08
simulation_functions
Rendered fromsimulation_functions.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2023-07-26
Started: 2022-09-23
t-test Application
Rendered fromttest_Vignette.Rmdusingknitr::rmarkdownon Apr 02 2025.Last update: 2024-10-04
Started: 2023-09-08
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Example simulation functions | example.simfun |
| Results of the extensions vignette | extensions_results |
| Find optimal study designs | find.design |
| Plot search result | plot.designresult |
| Print Summary of the search result | print.summary.designresult |
| Display info on the generated data | simulations_data |
| Summary of the search result | summary.designresult |
