{ "_id": "6abee8ae99f7aa8c6aa57eab", "Type": "Package", "Package": "hce", "Title": "Design and Analysis of Hierarchical Composite Endpoints", "Version": "0.9.4.5", "Authors@R": "person(\"Samvel B.\", \"Gasparyan\", , \"gasparyan.co@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-4797-2208\"))", "Description": "Simulate and analyze hierarchical composite endpoints with\nunivariate distributions by Gasparyan, Koch, Brunner in (2026)\nin “The Univariate Distribution of Hierarchical Composite\nEndpoints and the Condorcet Non-transitivity Paradox.”\n(Biometrical Journal 68 (3), ).\nIncludes implementation for the kidney hierarchical composite\nendpoint as defined in Heerspink HL et al (2023) “Development\nand validation of a new hierarchical composite end point for\nclinical trials of kidney disease progression” (Journal of the\nAmerican Society of Nephrology 34 (2): 2025–2038,\n). Win odds, also called\nWilcoxon-Mann-Whitney or success odds, is the main analysis\nmethod, but other win statistics (win probability, win ratio,\nnet benefit) are also implemented in the univariate case. The\nwin probability analysis is based on the Brunner-Munzel test\nand uses the DeLong-DeLong-Clarke-Pearson variance estimator,\nas described by Brunner and Konietschke (2025) in “An unbiased\nrank-based estimator of the Mann–Whitney variance including the\ncase of ties” (Statistical Papers 66 (1): 20,\n). Includes implementation of a\nnew Wilson-type, compatible confidence interval for the win\nodds, as proposed by Schüürhuis, Konietschke, Brunner (2025) in\n“A new approach to the nonparametric Behrens–Fisher problem\nwith compatible confidence intervals.” (Biometrical Journal 67\n(6), ). Stratification and covariate\nadjustment are performed based on the methodology presented by\nKoch GG et al. in “Issues for covariance analysis of\ndichotomous and ordered categorical data from randomized\nclinical trials and non-parametric strategies for addressing\nthem” (Statistics in Medicine 17 (15-16): 1863–92). For a\nreview, see Gasparyan SB et al (2021) “Adjusted win ratio with\nstratification: Calculation methods and interpretation”\n(Statistical Methods in Medical Research 30 (2): 580–611,\n).", "License": "MIT + file LICENSE", "BugReports": "https://github.com/Samve/hce/issues", "Encoding": "UTF-8", "LazyData": "true", "Roxygen": "list(markdown = TRUE)", "VignetteBuilder": "knitr", "Config/roxygen2/version": "8.1.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-01 23:08:34 UTC", "User": "root" }, "Author": "Samvel B. Gasparyan [aut, cre] (ORCID:\n)", "Maintainer": "Samvel B. Gasparyan ", "Repository": "https://samve.r-universe.dev", "Date/Publication": "2026-10-01 19:02:13 UTC", "RemoteUrl": "https://github.com/samve/hce", "RemoteRef": "HEAD", "RemoteSha": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "_user": "samve", "_type": "src", "_file": "hce_0.9.4.5.tar.gz", "_fileid": "https://r2.ropensci.org/ae8d13819df8be628d714fed6433c45d7c3771030391e4f92eceb5ae2fc5103e", "_filesize": 3697937, "_sha256": "ae8d13819df8be628d714fed6433c45d7c3771030391e4f92eceb5ae2fc5103e", "_expires": "2027-01-09T23:11:39.000Z", "_created": "2026-10-01T23:08:34.000Z", "_published": "2026-10-01T23:11:42.615Z", "_jobs": [ { "job": 110626490028, "time": 136, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11199985770" }, { "job": 110626490146, "time": 111, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11198978647" }, { "job": 110626490069, "time": 107, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11199172648" }, { "job": 110626490025, "time": 81, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11200015455" }, { "job": 110625225936, "time": 252, "config": "source", "r": "4.6.1", "check": "ERROR", "artifact": "11199810809" }, { "job": 110626489989, "time": 101, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11199806289" }, { "job": 110626490077, "time": 86, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11198988277" }, { "job": 110626490127, "time": 84, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11200035304" }, { "job": 110626490052, "time": 106, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11199486401" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214", "_status": "failure", "_upstream": "https://github.com/samve/hce", "_commit": { "id": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "author": "Samvel B. Gasparyan ", "committer": "GitHub ", "message": "Merge pull request #74 from Samve/version_20261001\n\nGLL documentation and updates/tests.", "time": 1790881333 }, "_maintainer": { "name": "Samvel B. Gasparyan", "email": "gasparyan.co@gmail.com", "orcid": "0000-0002-4797-2208" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "base", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" } ], "_owner": "samve", "_selfowned": true, "_usedby": 1, "_updates": [ { "week": "2025-41", "n": 2 }, { "week": "2025-47", "n": 2 }, { "week": "2025-49", "n": 6 }, { "week": "2026-04", "n": 1 }, { "week": "2026-05", "n": 1 }, { "week": "2026-06", "n": 1 }, { "week": "2026-07", "n": 1 }, { "week": "2026-10", "n": 1 }, { "week": "2026-11", "n": 1 }, { "week": "2026-19", "n": 1 }, { "week": "2026-20", "n": 1 }, { "week": "2026-26", "n": 1 }, { "week": "2026-40", "n": 1 } ], "_tags": [], "_stars": 0, "_contributors": [ { "user": "samve", "count": 127, "uuid": 10420380 }, { "user": "kevander", "count": 1, "uuid": 7585389 } ], "_userbio": { "uuid": 10420380, "type": "user", "name": "Samvel B. Gasparyan", "followers": 8, "description": "Clinical Trialist Statistician\r\nhttps://orcid.org/0000-0002-4797-2208" }, "_downloads": { "count": 583, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/hce" }, "_devurl": "https://github.com/samve/hce", "_searchresults": 35, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/hce.html", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "LICENSE" ], "_homeurl": "https://github.com/samve/hce", "_realowner": "samve", "_cranurl": true, "_releases": [ { "version": "0.0.2", "date": "2022-09-26" }, { "version": "0.0.8", "date": "2022-11-16" }, { "version": "0.4.0", "date": "2023-01-05" }, { "version": "0.5.0", "date": "2023-01-16" }, { "version": "0.5.8", "date": "2023-08-17" }, { "version": "0.5.9", "date": "2023-10-31" }, { "version": "0.6.0", "date": "2024-03-12" }, { "version": "0.6.3", "date": "2024-08-19" }, { "version": "0.6.5", "date": "2024-10-16" }, { "version": "0.6.7", "date": "2025-01-07" }, { "version": "0.7.0", "date": "2025-03-05" }, { "version": "0.7.2", "date": "2025-05-14" }, { "version": "0.8.0", "date": "2025-07-11" }, { "version": "0.8.5", "date": "2025-08-22" }, { "version": "0.8.8", "date": "2025-12-11" }, { "version": "0.9.0", "date": "2026-01-29" }, { "version": "0.9.1", "date": "2026-03-12" }, { "version": "0.9.3", "date": "2026-05-13" }, { "version": "0.9.4", "date": "2026-06-26" } ], "_exports": [ "as_formulae", "as_hce", "calcWINS", "calcWO", "deltaWO", "dGLL", "hce", "hGLL", "HGLL", "IWP", "minWO", "oGLL", "pGLL", "powerWO", "propWINS", "qGLL", "regWO", "rGLL", "rweibullGF", "simHCE", "simKHCE", "simORD", "simTTE", "sizeWO", "sizeWR", "stratWO", "summaryWO" ], "_datasets": [ { "name": "ADET", "title": "Event-Time dataset for kidney outcomes.", "object": "ADET", "class": [ "data.frame" ], "fields": [ "ID", "AVAL", "PARAM", "PARAMCD", "PARAMN", "TRTPN" ], "rows": 604, "table": true, "tojson": true }, { "name": "ADLB", "title": "Laboratory dataset for Glomerular Filtration Rate (GFR) measurements.", "object": "ADLB", "class": [ "data.frame" ], "fields": [ "ID", "TRTPN", "AVAL", "ADAY", "AVISITN", "PARAM", "PARAMCD", "PARAMN" ], "rows": 13980, "table": true, "tojson": true }, { "name": "ADSL", "title": "Baseline characteristics dataset of patients with kidney function assessments.", "object": "ADSL", "class": [ "data.frame" ], "fields": [ "ID", "TRTPN", "EGFRBL", "STRATAN" ], "rows": 1500, "table": true, "tojson": true }, { "name": "COVID19", "title": "COVID-19 ordinal scale dataset (full report).", "object": "COVID19", "class": [ "data.frame" ], "fields": [ "TRTP", "GROUP" ], "rows": 1062, "table": true, "tojson": true }, { "name": "COVID19b", "title": "COVID-19 ordinal scale dataset (preliminary report).", "object": "COVID19b", "class": [ "data.frame" ], "fields": [ "TRTP", "GROUP" ], "rows": 844, "table": true, "tojson": true }, { "name": "COVID19plus", "title": "COVID-19 ordinal scale dataset for a combination therapy.", "object": "COVID19plus", "class": [ "data.frame" ], "fields": [ "ID", "TRTP", "GROUP", "BASE" ], "rows": 1033, "table": true, "tojson": true }, { "name": "HCE1", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "object": "HCE1", "class": [ "data.frame" ], "fields": [ "ID", "TRTP", "GROUP", "GROUPN", "AVALT", "AVAL0", "AVAL", "PADY" ], "rows": 1000, "table": true, "tojson": true }, { "name": "HCE2", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "object": "HCE2", "class": [ "data.frame" ], "fields": [ "ID", "TRTP", "GROUP", "GROUPN", "AVALT", "AVAL0", "AVAL", "PADY" ], "rows": 1000, "table": true, "tojson": true }, { "name": "HCE3", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "object": "HCE3", "class": [ "data.frame" ], "fields": [ "ID", "TRTP", "GROUP", "GROUPN", "AVALT", "AVAL0", "AVAL", "PADY" ], "rows": 1000, "table": true, "tojson": true }, { "name": "HCE4", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "object": "HCE4", "class": [ "data.frame" ], "fields": [ "ID", "TRTP", "GROUP", "GROUPN", "AVALT", "AVAL0", "AVAL", "PADY" ], "rows": 1000, "table": true, "tojson": true }, { "name": "KHCE", "title": "Kidney Hierarchical Composite Endpoint dataset.", "object": "KHCE", "class": [ "data.frame" ], "fields": [ "ID", "AVAL0", "GROUP", "PARAMCD", "PARAMN", "GROUPN", "AVAL", "TRTPN", "EGFRBL", "STRATAN", "TRTP", "PADY" ], "rows": 1500, "table": true, "tojson": true } ], "_help": [ { "page": "ADET", "title": "Event-Time dataset for kidney outcomes.", "topics": [ "ADET" ] }, { "page": "ADLB", "title": "Laboratory dataset for Glomerular Filtration Rate (GFR) measurements.", "topics": [ "ADLB" ] }, { "page": "ADSL", "title": "Baseline characteristics dataset of patients with kidney function assessments.", "topics": [ "ADSL" ] }, { "page": "as_hce", "title": "A generic function for coercing data structures to 'hce' objects", "topics": [ "as_hce" ] }, { "page": "as_hce.data.frame", "title": "Coerce a data frame to an 'hce' object", "topics": [ "as_hce.data.frame" ] }, { "page": "as_hce.default", "title": "Coerce a data frame to an 'hce' object", "topics": [ "as_hce.default" ] }, { "page": "calcWINS", "title": "A generic function for calculating win statistics", "topics": [ "calcWINS" ] }, { "page": "calcWINS.data.frame", "title": "Win statistics calculation using a data frame", "topics": [ "calcWINS.data.frame" ] }, { "page": "calcWINS.formula", "title": "Win statistics calculation using formula syntax", "topics": [ "calcWINS.formula" ] }, { "page": "calcWINS.hce", "title": "Win statistics calculation for 'hce' objects", "topics": [ "calcWINS.hce" ] }, { "page": "calcWO", "title": "A generic function for calculating win odds", "topics": [ "calcWO" ] }, { "page": "calcWO.data.frame", "title": "Win odds calculation using a data frame", "topics": [ "calcWO.data.frame" ] }, { "page": "calcWO.formula", "title": "Win odds calculation using formula syntax", "topics": [ "calcWO.formula" ] }, { "page": "calcWO.hce", "title": "Win odds calculation for 'hce' objects", "topics": [ "calcWO.hce" ] }, { "page": "COVID19", "title": "COVID-19 ordinal scale dataset (full report).", "topics": [ "COVID19" ] }, { "page": "COVID19b", "title": "COVID-19 ordinal scale dataset (preliminary report).", "topics": [ "COVID19b" ] }, { "page": "COVID19plus", "title": "COVID-19 ordinal scale dataset for a combination therapy.", "topics": [ "COVID19plus" ] }, { "page": "deltaWO", "title": "A generic function for calculating win odds based on a threshold", "topics": [ "deltaWO" ] }, { "page": "deltaWO.adhce", "title": "Win odds calculation based on a threshold for 'adhce' objects", "topics": [ "deltaWO.adhce" ] }, { "page": "formulae", "title": "Decompose formula objects", "topics": [ "as_formulae", "as_formulae.formula", "formulae" ] }, { "page": "GLL", "title": "The Generalized Log-Logistic Distribution", "topics": [ "dGLL", "GLL", "HGLL", "hGLL", "oGLL", "pGLL", "qGLL", "rGLL" ] }, { "page": "hce", "title": "Helper function for 'hce' objects", "topics": [ "hce" ] }, { "page": "HCE1", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "topics": [ "HCE1" ] }, { "page": "HCE2", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "topics": [ "HCE2" ] }, { "page": "HCE3", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "topics": [ "HCE3" ] }, { "page": "HCE4", "title": "'HCE1', 'HCE2', 'HCE3', 'HCE4' datasets for 1000 patients with different treatment effects.", "topics": [ "HCE4" ] }, { "page": "IWP", "title": "Calculates patient-level individual win proportions", "topics": [ "IWP" ] }, { "page": "KHCE", "title": "Kidney Hierarchical Composite Endpoint dataset.", "topics": [ "KHCE" ] }, { "page": "minWO", "title": "Minimum detectable or WO for alternative hypothesis for given power (no ties)", "topics": [ "minWO" ] }, { "page": "plot.hce", "title": "A plot method for 'hce' objects", "topics": [ "plot.hce" ] }, { "page": "plot.hce_results", "title": "A print method for 'hce_results ' objects", "topics": [ "plot.hce_results" ] }, { "page": "powerWO", "title": "Power calculation for the win odds test (no ties)", "topics": [ "powerWO" ] }, { "page": "print.hce_results", "title": "A print method for 'hce_results' objects", "topics": [ "print.hce_results" ] }, { "page": "propWINS", "title": "Proportion of wins/losses/ties given the win odds and the win ratio", "topics": [ "propWINS" ] }, { "page": "regWO", "title": "A generic function for win odds regression", "topics": [ "regWO" ] }, { "page": "regWO.data.frame", "title": "Win Odds Regression Using a Data Frame", "topics": [ "regWO.data.frame" ] }, { "page": "regWO.formula", "title": "Win Odds Regression Using a Formula Syntax", "topics": [ "regWO.formula" ] }, { "page": "rweibullGF", "title": "Simulate random numbers from a Weibull distribution with gamma frailty", "topics": [ "rweibullGF" ] }, { "page": "simHCE", "title": "Simulate an 'hce' object", "topics": [ "simHCE" ] }, { "page": "simKHCE", "title": "Simulate a kidney disease 'hce' dataset", "topics": [ "simKHCE" ] }, { "page": "simORD", "title": "Simulate ordinal variables for two treatment groups using categorization of beta distributions", "topics": [ "simORD" ] }, { "page": "simTTE", "title": "Simulate an 'adhce' dataset under an illness-death model with two correlated outcomes", "topics": [ "simTTE" ] }, { "page": "sizeWO", "title": "Sample size calculation for the win odds test (no ties)", "topics": [ "sizeWO" ] }, { "page": "sizeWR", "title": "Sample size calculation for the win ratio test (with WR = 1 null hypothesis)", "topics": [ "sizeWR" ] }, { "page": "stratWO", "title": "A generic function for stratified win odds with adjustment", "topics": [ "stratWO" ] }, { "page": "stratWO.data.frame", "title": "Stratified win odds with adjustment", "topics": [ "stratWO.data.frame" ] }, { "page": "stratWO.formula", "title": "Stratified win odds with adjustment using formula", "topics": [ "stratWO.formula" ] }, { "page": "summaryWO", "title": "A generic function for summarizing win odds", "topics": [ "summaryWO" ] }, { "page": "summaryWO.adhce", "title": "Win odds summary for 'adhce' objects", "topics": [ "summaryWO.adhce" ] }, { "page": "summaryWO.data.frame", "title": "Win odds summary for a data frame", "topics": [ "summaryWO.data.frame" ] }, { "page": "summaryWO.formula", "title": "Win odds summary using formula syntax", "topics": [ "summaryWO.formula" ] }, { "page": "summaryWO.hce", "title": "Win odds summary for 'hce' objects", "topics": [ "summaryWO.hce" ] } ], "_pkglogo": "https://github.com/samve/hce/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/samve/hce/raw/HEAD/README.md", "_rundeps": [], "_vignettes": [ { "source": "GLL.Rmd", "filename": "GLL.html", "title": "Generalized Log-Logistic Distributions", "author": "Samvel B. Gasparyan", "engine": "knitr::rmarkdown", "headings": [ "Setup", "Background", "Weibull distribution conditional on gamma frailty", "$$S(t \\mid \\xi)", "\\exp", "Time-dependent hazard ratio", "$$h(t \\mid \\lambda, \\alpha, \\theta)", "$$HR(t)", "Time-dependent survival odds ratio", "Time-invariant quantile ratio", "$$Q(p \\mid \\lambda,\\alpha,\\theta)", "$$Q(p \\mid \\lambda,\\alpha,\\theta=0)", "$$QR(p)", "\\frac", "$$\\frac", "\\frac", "References" ], "created": "2026-10-01 19:02:13", "modified": "2026-10-01 19:02:13", "commits": 1 }, { "source": "hce.Rmd", "filename": "hce.html", "title": "Hierarchical composite endpoints", "author": "Samvel B. Gasparyan", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Setup", "Definitions", "Examples", "Kidney HCE", "COVID-19", "Heart Failure", "Simulations", "The kidney HCE", "Dependent Time-To-Event Outcomes", "Joint Distribution Modeling Using Copulas", "The Marshall-Olkin algorithm", "Chambers-Mallows-Stuck method for simulating stable random variables", "Note", "Implementation", "References" ], "created": "2023-08-03 07:44:49", "modified": "2026-10-01 19:02:13", "commits": 12 }, { "source": "Introduction.Rmd", "filename": "Introduction.html", "title": "Introduction", "author": "Samvel B. Gasparyan", "engine": "knitr::rmarkdown", "headings": [ "hce package intro", "Background", "Setup", "Contents", "In Brief", "Calculations", "Univariate hierarchical composite endpoints", "Thresholds", "Simulations", "Power and sample size", "Ordinal dominance graph and the maraca plot", "Extras", "Helpers", "hce Objects", "hce() Function", "Create an hce Object from a Data Frame", "Simulate hce Objects Using simHCE()", "Generics for hce Objects", "References" ], "created": "2022-10-16 13:24:25", "modified": "2026-06-26 17:45:10", "commits": 22 }, { "source": "maraca.Rmd", "filename": "maraca.html", "title": "Visualization of HCE using maraca plots", "author": "Samvel B. Gasparyan", "engine": "knitr::rmarkdown", "headings": [ "Visualization", "Setup", "The Maraca Plot", "References" ], "created": "2023-10-31 17:12:38", "modified": "2026-10-01 19:02:13", "commits": 5 }, { "source": "Wins.Rmd", "filename": "Wins.html", "title": "Win statistics", "author": "Samvel B. Gasparyan", "engine": "knitr::rmarkdown", "headings": [ "Win Odds, Win Ratio, and Net Benefit", "Setup", "Terminology", "Definitions", "References" ], "created": "2023-01-07 22:13:39", "modified": "2026-10-01 19:02:13", "commits": 10 } ], "_score": 6.533072660048813, "_indexed": true, "_nocasepkg": "hce", "_universes": [ "samve" ], "_previous": "0.9.4", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.9.4.5", "date": "2026-10-01T23:10:46.000Z", "distro": "resolute", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/e1eb3841ce19b07df9db9facc27ad469c654fa976e0ec541e14fc6031b977d1b", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" }, { "r": "4.6.1", "os": "linux", "version": "0.9.4.5", "date": "2026-10-01T23:10:28.000Z", "distro": "resolute", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/83c4834f564784355756e0c00a5706d250a4d9c72cf01092ebee35fcc9a77df1", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" }, { "r": "4.5.3", "os": "mac", "version": "0.9.4.5", "date": "2026-10-01T23:10:31.000Z", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/a0e5ad1780c7716c3e5b3a6ee4489393168617b5817cf4ecc31e08fe6c2cfebe", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" }, { "r": "4.6.1", "os": "mac", "version": "0.9.4.5", "date": "2026-10-01T23:10:08.000Z", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/2ca55f2ce91f6e39a329f21b2a0251c0f6055bb842478d0009019e38f1cc2185", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" }, { "r": "4.6.0", "os": "wasm", "version": "0.9.4.5", "date": "2026-10-01T23:10:38.000Z", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/af78ec5bce5dc434293708db9961d0dba33c5a772e386b16db980e6008083add", "status": "success", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" }, { "r": "4.7.0", "os": "win", "version": "0.9.4.5", "date": "2026-10-01T23:09:49.000Z", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/f67d1f2e89813d18dd14d2005a4a4935914dcc02d164cfc0d8114a78591f27d1", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" }, { "r": "4.5.3", "os": "win", "version": "0.9.4.5", "date": "2026-10-01T23:09:54.000Z", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/ec2e633384318ea9562765dfc4ec0e3638097f96a9199bc6e49c66ced8135894", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" }, { "r": "4.6.1", "os": "win", "version": "0.9.4.5", "date": "2026-10-01T23:10:07.000Z", "commit": "0a5c51eeb9e281b4ff506ea30aa859f1e737659c", "fileid": "https://r2.ropensci.org/138370705e1606de1669184e7f7cfac06f54a6a89d9193910f515af1282750bd", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/samve/actions/runs/36938755214" } ] }