{ "_id": "6a12c50dacfb0bcc41d1f5c2", "Package": "mpower", "Type": "Package", "Title": "Power Analysis via Monte Carlo Simulation for Correlated Data", "Version": "0.1.0", "Authors@R": "person(given = \"Phuc H.\",\nfamily = \"Nguyen\",\nrole = c(\"aut\", \"cre\"),\nemail = \"phuc.nguyen.rcran@gmail.com\",\ncomment = c(ORCID = \"0000-0002-6206-0194\"))", "Description": "A flexible framework for power analysis using Monte Carlo\nsimulation for settings in which considerations of the\ncorrelations between predictors are important. Users can set up\na data generative model that preserves dependence structures\namong predictors given existing data (continuous, binary, or\nordinal). Users can also generate power curves to assess the\ntrade-offs between sample size, effect size, and power of a\ndesign. This package includes several statistical models common\nin environmental mixtures studies. For more details and\ntutorials, see Nguyen et al. (2022) .", "License": "LGPL", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.2.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-24 09:25:55 UTC", "User": "root" }, "Author": "Phuc H. Nguyen [aut, cre]\n()", "Maintainer": "Phuc H. Nguyen ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2022-09-21 07:50:05 UTC", "RemoteUrl": "https://github.com/cran/mpower", "RemoteRef": "HEAD", "RemoteSha": "3eba894dc18b5ce2779a11beee96d3c5f77be1c0", "MD5sum": "6d0b7b5a3b7f86098c68ec15df37932d", "_user": "cran", "_type": "src", "_file": "mpower_0.1.0.tar.gz", "_fileid": "252e5f76727ffd9ed3a9654b67821af22f5bdea5a57395c98ad8984bfd5b6cd2", "_filesize": 1017878, "_sha256": "252e5f76727ffd9ed3a9654b67821af22f5bdea5a57395c98ad8984bfd5b6cd2", "_created": "2026-05-24T09:25:55.000Z", "_published": "2026-05-24T09:29:49.093Z", "_distro": "noble", "_jobs": [ { "job": 77586922661, "time": 199, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7184031438" }, { "job": 77586922650, "time": 184, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7184029945" }, { "job": 77586702851, "time": 239, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7184011563" }, { "job": 77586922657, "time": 166, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7184028030" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/26357447420", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/mpower", "_commit": { "id": "3eba894dc18b5ce2779a11beee96d3c5f77be1c0", "author": "Phuc H. Nguyen ", "committer": "cran-robot ", "message": "version 0.1.0\n", "time": 1663746605 }, "_maintainer": { "name": "Phuc H. Nguyen", "email": "phuc.nguyen.rcran@gmail.com", "orcid": "0000-0002-6206-0194" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "abind", "role": "Imports" }, { "package": "boot", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "doSNOW", "role": "Imports" }, { "package": "foreach", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "MASS", "role": "Imports" }, { "package": "magrittr", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "purrr", "role": "Imports" }, { "package": "snow", "role": "Imports" }, { "package": "sbgcop", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "reshape2", "role": "Imports" }, { "package": "tibble", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "tidyselect", "role": "Imports" }, { "package": "BMA", "role": "Suggests" }, { "package": "bkmr", "role": "Suggests" }, { "package": "bws", "role": "Suggests" }, { "package": "infinitefactor", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "NHANES", "role": "Suggests" }, { "package": "qgcomp", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "rstan", "role": "Suggests" }, { "package": "testthat", "role": "Suggests" }, { "package": "openxlsx", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 1, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 267, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/mpower" }, "_searchresults": 13, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/mpower.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2022-09-21" } ], "_exports": [ "bkmr_wrapper", "bma_wrapper", "bws_wrapper", "estimate_snr", "fin_wrapper", "fit", "genx", "geny", "glm_wrapper", "InferenceModel", "MixtureModel", "mplot", "OutcomeModel", "plot_summary", "qgcomp_lin_wrapper", "qmultinom", "scale_f", "scale_sigma", "sim_curve", "sim_power", "summary" ], "_datasets": [ { "name": "nhanes1518", "title": "NHANES data from 2015-2016 and 2017-2018 cycles", "object": "nhanes1518", "class": [ "tbl_df", "tbl", "data.frame" ], "fields": [ "SEQN", "WTINT2YR", "WTMEC2YR", "RIDSTATR", "RIAGENDR", "RIDAGEYR", "INDFMPIR", "RIDRETH1", "DMDEDUC2", "DMDEDUC3", "INDHHIN2", "BMXBMI", "BMXWAIST", "BMXWT", "BMXHT", "URXUCR", "WTSB2YR", "URXCNP", "URDCNPLC", "URXCOP", "URDCOPLC", "URXECP", "URDECPLC", "URXHIBP", "URDHIBLC", "URXMBP", "URDMBPLC", "URXMC1", "URDMC1LC", "URXMCOH", "URDMCOLC", "URXMEP", "URDMEPLC", "URXMHBP", "URDMHBLC", "URXMHH", "URDMHHLC", "URXMHNC", "URDMCHLC", "URXMHP", "URDMHPLC", "URXMIB", "URDMIBLC", "URXMNP", "URDMNPLC", "URXMOH", "URDMOHLC", "URXMZP", "URDMZPLC", "WTINT4YR", "WTMEC4YR", "WTSB4YR" ], "rows": 19225, "table": true, "tojson": true } ], "_help": [ { "page": "bkmr_wrapper", "title": "Fits a BKMR model with significance criteria: PIP and group-wise PIP", "topics": [ "bkmr_wrapper" ] }, { "page": "bma_wrapper", "title": "Fits a linear model with Bayesian model selection with significance criteria: PIP and posterior probability of nonzero coefficients being on one side of zero.", "topics": [ "bma_wrapper" ] }, { "page": "bws_wrapper", "title": "Fits a Bayesian weighted sums", "topics": [ "bws_wrapper" ] }, { "page": "cor2partial", "title": "Convert a correlation matrix into a partial correlation matrix", "topics": [ "cor2partial" ] }, { "page": "cvine", "title": "Citation: Daniel Lewandowski, Dorota Kurowicka, Harry Joe, Generating random correlation matrices based on vines and extended onion method, Journal of Multivariate Analysis, Volume 100, Issue 9, 2009, Pages 1989-2001, ISSN 0047-259X, https://doi.org/10.1016/j.jmva.2009.04.008.", "topics": [ "cvine" ] }, { "page": "estimate_snr", "title": "Monte Carlo approximation of the SNR", "topics": [ "estimate_snr" ] }, { "page": "fin_wrapper", "title": "Fits a Bayesian factor model with interactions", "topics": [ "fin_wrapper" ] }, { "page": "fit", "title": "Fits the model to given data and gets a list of significance criteria", "topics": [ "fit" ] }, { "page": "genx", "title": "Generates a matrix of n observations of p predictors", "topics": [ "genx" ] }, { "page": "geny", "title": "Generates a vector of outcomes", "topics": [ "geny" ] }, { "page": "glm_wrapper", "title": "Fits a generalized linear model", "topics": [ "glm_wrapper" ] }, { "page": "InferenceModel", "title": "Statistical model that returns significance criterion", "topics": [ "InferenceModel" ] }, { "page": "MixtureModel", "title": "Correlated predictors generator", "topics": [ "MixtureModel" ] }, { "page": "mplot", "title": "Visualize marginals and Gaussian copula correlations of simulated data", "topics": [ "mplot" ] }, { "page": "mpower", "title": "mpower: Power analysis using Monte Carlo for correlated predictors.", "topics": [ "mpower" ] }, { "page": "nhanes1518", "title": "NHANES data from 2015-2016 and 2017-2018 cycles", "topics": [ "nhanes1518" ] }, { "page": "OutcomeModel", "title": "Outcome generator", "topics": [ "OutcomeModel" ] }, { "page": "partial", "title": "Partial correlations between elements in x and elements in y", "topics": [ "partial" ] }, { "page": "plot_summary", "title": "Plot summaries of power simulation", "topics": [ "plot_summary" ] }, { "page": "qgcomp_lin_wrapper", "title": "Fits a linear Quantile G-Computation model with no interactions", "topics": [ "qgcomp_lin_wrapper" ] }, { "page": "qmultinom", "title": "Quantile function for the multinomial distribution, size = 1", "topics": [ "qmultinom" ] }, { "page": "rsq2snr", "title": "Convert R-squared value to the SNR", "topics": [ "rsq2snr" ] }, { "page": "scale_f", "title": "Rescale the mean function of an OutcomeModel to meet a given SNR", "topics": [ "scale_f" ] }, { "page": "scale_sigma", "title": "Rescale the noise variance of a Gaussian OutcomeModel to meet a given SNR", "topics": [ "scale_sigma" ] }, { "page": "set_value", "title": "This function updates values in an OutcomeModel object", "topics": [ "set_value" ] }, { "page": "sim_curve", "title": "Power curve using Monte Carlo simulation", "topics": [ "sim_curve" ] }, { "page": "sim_power", "title": "Power analysis using Monte Carlo simulation", "topics": [ "sim_power" ] }, { "page": "summary", "title": "Tabular summaries of power simulation", "topics": [ "summary" ] } ], "_readme": "https://github.com/cran/mpower/raw/HEAD/README.md", "_rundeps": [ "abind", "boot", "cli", "codetools", "cpp11", "doSNOW", "dplyr", "farver", "foreach", "generics", "ggplot2", "glue", "gtable", "isoband", "iterators", "labeling", "lifecycle", "magrittr", "MASS", "pillar", "pkgconfig", "plyr", "purrr", "R6", "RColorBrewer", "Rcpp", "reshape2", "rlang", "S7", "sbgcop", "scales", "snow", "stringi", "stringr", "tibble", "tidyr", "tidyselect", "utf8", "vctrs", "viridisLite", "withr" ], "_score": 1.8129133566428557, "_indexed": true, "_nocasepkg": "mpower", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.0", "date": "2026-05-24T09:28:54.000Z", "distro": "noble", "commit": "3eba894dc18b5ce2779a11beee96d3c5f77be1c0", "fileid": "7ba21169cfc5d6b94c0e0e1507348deba541d526a4ce251d5cf8b38acdbd02e0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26357447420" }, { "r": "4.6.0", "os": "linux", "version": "0.1.0", "date": "2026-05-24T09:28:42.000Z", "distro": "noble", "commit": "3eba894dc18b5ce2779a11beee96d3c5f77be1c0", "fileid": "8614102c894ede2e0daae2c691257d1a13c4140028b2063168b7c020f7ed1baf", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26357447420" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.0", "date": "2026-05-24T09:28:57.000Z", "commit": "3eba894dc18b5ce2779a11beee96d3c5f77be1c0", "fileid": "48974397b569899e1b0d03fde84ddce6a51bfb129192d1f1ed830301e02440ca", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/26357447420" } ] }