{ "_id": "6a103d45acfb0bcc41c9c394", "Package": "genpwr", "Title": "Power Calculations Under Genetic Model Misspecification", "Version": "1.0.4", "Authors@R": "c(person(\"Camille\", \"Moore\", email = \"moorec@njhealth.org\", \nrole = c(\"aut\", \"cre\")), person(\"Sean\", \"Jacobson\", email = \"jacobsons@njhealth.org\",\nrole = \"aut\"))", "Description": "Power and sample size calculations for genetic association\nstudies allowing for misspecification of the model of genetic\nsusceptibility. \"Hum Hered.\n2019;84(6):256-271.. Epub 2020 Jul 28.\"\nPower and/or sample size can be calculated for logistic\n(case/control study design) and linear (continuous phenotype)\nregression models, using additive, dominant, recessive or\ndegree of freedom coding of the genetic covariate while\nassuming a true dominant, recessive or additive genetic effect.\nIn addition, power and sample size calculations can be\nperformed for gene by environment interactions. These methods\nare extensions of Gauderman (2002) \nand Gauderman (2002) and are described\nin: Moore CM, Jacobson S, Fingerlin TE. Power and Sample Size\nCalculations for Genetic Association Studies in the Presence of\nGenetic Model Misspecification. American Society of Human\nGenetics. October 2018, San Diego.", "License": "GPL-3", "Encoding": "UTF-8", "RoxygenNote": "7.1.1", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-11 09:47:06 UTC", "User": "root" }, "Author": "Camille Moore [aut, cre], Sean Jacobson [aut]", "Maintainer": "Camille Moore ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2021-03-30 23:00:07 UTC", "RemoteUrl": "https://github.com/cran/genpwr", "RemoteRef": "HEAD", "RemoteSha": "51c256c4ce838a132b56287b63a6db579eb925b0", "MD5sum": "adbc5402002cf336fe4fa76e51932b58", "_user": "cran", "_type": "src", "_file": "genpwr_1.0.4.tar.gz", "_fileid": "752113b49f0143eecc19db3f5d9389a73aabb5e40dbaf97081b4455b1eb03265", "_filesize": 1018615, "_sha256": "752113b49f0143eecc19db3f5d9389a73aabb5e40dbaf97081b4455b1eb03265", "_created": "2026-05-11T09:47:06.000Z", "_published": "2026-05-22T11:25:57.414Z", "_distro": "noble", "_jobs": [ { "job": 77370169455, "time": 149, "config": "linux-devel-x86_64", "r": 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"role": "Imports" }, { "package": "MASS", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 1, "_updates": [], "_tags": [], "_stars": 1, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 86, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/genpwr" }, "_mentions": 4, "_searchresults": 41, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/genpwr.html", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "1.0.0", "date": "2019-04-04" }, { "version": "1.0.1", "date": "2019-09-17" }, { 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"null.ll", "null.ll.linear", "odds_ratio_function", "or_calc", "or.function.2df", "or.plot", "p_vec_returner", "p_vec_returner_lin_env", "power_envir.calc", "power_envir.calc.linear_outcome", "power_linear_envir.calc.linear_outcome", "power_linear_envir.calc.logistic_outcome", "power.calc", "power.calc.linear", "power.plot", "quad_roots", "rec.fun.t", "rec.or.function", "recessive.ll", "recessive.ll.linear", "solve_a", "ss_envir.calc", "ss_envir.calc.linear_outcome", "ss_linear_envir.calc.linear_outcome", "ss_linear_envir.calc.logistic_outcome", "ss.calc", "ss.calc.linear", "ss.plot", "X_mat_returner", "X_mat_returner_lle", "zero_finder_nleqslv" ], "_help": [ { "page": "add.fun.t", "title": "Function to Calculate t matrix for logistic outcome with binary environment interaction in additive model", "topics": [ "add.fun.t" ] }, { "page": "add.or.function", "title": "Additive Model Function", "topics": [ "add.or.function" ] }, { "page": "additive.ll", "title": "Function to Calculate 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for a Single Genotype", "topics": [ "expected.linear.ll" ] }, { "page": "expected.linear.ll.lin.env", "title": "Function to Calculate Expected Log Likelihood for a Single Genotype with linear environment interaction", "topics": [ "expected.linear.ll.lin.env" ] }, { "page": "find.prob.dom", "title": "Dominant probability finding function", "topics": [ "find.prob.dom" ] }, { "page": "find.prob.rec", "title": "Recessive probability finding function", "topics": [ "find.prob.rec" ] }, { "page": "genpwr.calc", "title": "Function to Calculate Power for Linear Models with logistic environment interaction", "topics": [ "genpwr.calc" ] }, { "page": "integrand_funct_case", "title": "Function to generate integrand for mle for cases", "topics": [ "integrand_funct_case" ] }, { "page": "integrand_funct_control", "title": "Function to generate integrand for mle for controls", "topics": [ "integrand_funct_control" ] }, { "page": "linear.mles", "title": "Function to calculate MLE's for linear models", 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logistic environment interaction", "topics": [ "power_envir.calc.linear_outcome" ] }, { "page": "power_linear_envir.calc.linear_outcome", "title": "Function to Calculate Power for Linear Models with linear environment interaction", "topics": [ "power_linear_envir.calc.linear_outcome" ] }, { "page": "power_linear_envir.calc.logistic_outcome", "title": "Function to Calculate Power for Linear Models with logistic environment interaction", "topics": [ "power_linear_envir.calc.logistic_outcome" ] }, { "page": "power.calc", "title": "Function to Calculate Power", "topics": [ "power.calc" ] }, { "page": "power.calc.linear", "title": "Function to Calculate Power for Linear Models", "topics": [ "power.calc.linear" ] }, { "page": "power.plot", "title": "Function to Plot Power Results", "topics": [ "power.plot" ] }, { "page": "quad_roots", "title": "Function to Solve Quadratic Equations", "topics": [ "quad_roots" ] }, { "page": "rec.fun.t", "title": "Function to Calculate t matrix for logistic 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interaction", "topics": [ "X_mat_returner_lle" ] }, { "page": "zero_finder_nleqslv", "title": "Zero finder", "topics": [ "zero_finder_nleqslv" ] } ], "_readme": "https://github.com/cran/genpwr/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "farver", "ggplot2", "glue", "gtable", "isoband", "labeling", "lifecycle", "MASS", "nleqslv", "R6", "RColorBrewer", "rlang", "S7", "scales", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "vignette.Rmd", "filename": "vignette.html", "title": "Introduction to genpwr", "engine": "knitr::rmarkdown", "headings": [ "Install genpwr", "Examples", "Power Calculation for a Case Control Study", "Sample Size Calculation for a Case Control Study", "Detectable Odds Ratio Calculation for a Case Control Study", "Power Calculation for a Case Control Study with a Gene x Environment Interaction", "Sample Size Calculation for a Case Control Study with a Gene x Environment Interaction" ], "created": "2019-04-04 16:40:03", "modified": "2019-04-04 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