{ "_id": "6ac30199d743750d376d9f26", "Package": "safestats", "Type": "Package", "Title": "Safe Anytime-Valid Inference", "Version": "0.8.9", "Date": "2026-10-02", "Authors@R": "c(\nperson(\"Alexander\", \"Ly\", email = \"alexander.ly.nl@gmail.com\",\nrole = c(\"cre\", \"aut\")),\nperson(\"Rosanne\", \"Turner\", email = \"rosanne.turner@cwi.nl\",\nrole = \"aut\"),\nperson(\"Yongqi\", \"Wang\", email = \"yongqi.wang@cwi.nl\",\nrole = \"aut\"),\nperson(\"Muriel Felipe\", \"Perez-Ortiz\", email = \"m.f.perez.ortiz@tue.nl\",\nrole = c(\"ctb\")),\nperson(\"Udo\", \"Boehm\", email = \"udo.boehm@cwi.nl\",\nrole = c(\"ctb\")),\nperson(\"Judith\", \"ter Schure\", email = \"Judith.ter.Schure@cwi.nl\",\nrole = c(\"ctb\")),\nperson(\"Peter\", \"Grunwald\", email = \"Peter.Grunwald@cwi.nl\",\nrole = c(\"ctb\"))\n)", "Maintainer": "Alexander Ly ", "Description": "Functions to design and apply tests that are anytime\nvalid. The functions can be used to design hypothesis tests in\nthe prospective/randomised control trial setting or in the\nobservational/retrospective setting. The resulting tests remain\nvalid under both optional stopping and optional continuation.\nThe current version includes safe t-tests and safe tests of two\nproportions. For details on the theory of safe tests, see Ly,\nA, Boehm, Grunwald, Ramdas and van Ravenzwaaij (2024). \"Safe\nAnytime-Valid Inference: Practical maximally flexible sampling\ndesigns for experiments based on e-values\"\n() and Grunwald, de Heide and Koolen\n(2024) \"Safe Testing\" (), for\ndetails on safe logrank tests see ter Schure, Perez-Ortiz, Ly\nand Grunwald (2024) \"The Anytime-Valid Logrank Test: Error\nControl under Continuous Monitoring with Unlimited Horizon\"\n(), and Turner, Ly and Grunwald\n(2024) \"Generic E-variables for exact sequential k-sample tests\nthat allow for optional stopping\"\n() for details on safe\ncontingency table tests.", "License": "LGPL (>= 3)", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Language": "en-GB", "Config/testthat/edition": "3", "Roxygen": "list(markdown = TRUE)", "Config/roxygen2/version": "8.1.0", "Config/pak/sysreqs": "cmake make pari-gp", "Repository": "https://alexanderlynl.r-universe.dev", "Date/Publication": "2026-10-04 22:52:54 UTC", "RemoteUrl": "https://github.com/alexanderlynl/safestats", "RemoteRef": "HEAD", "RemoteSha": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "Packaged": { "Date": "2026-10-05 01:42:20 UTC", "User": "root" }, "Author": "Alexander Ly [cre, aut],\nRosanne Turner [aut],\nYongqi Wang [aut],\nMuriel Felipe Perez-Ortiz [ctb],\nUdo Boehm [ctb],\nJudith ter Schure [ctb],\nPeter Grunwald [ctb]", "_user": "alexanderlynl", "_type": "src", "_file": "safestats_0.8.9.tar.gz", "_fileid": "https://r2.ropensci.org/cf040b05e6499e1f4350e82ec95ab85ed80215c466f92fe415ba0832ab43b271", "_filesize": 2948279, "_sha256": "cf040b05e6499e1f4350e82ec95ab85ed80215c466f92fe415ba0832ab43b271", "_expires": "2027-01-13T01:47:03.000Z", "_created": "2026-10-05T01:42:20.000Z", "_published": "2026-10-05T01:47:05.370Z", "_jobs": [ { "job": 111582829281, "time": 201, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11321326403" }, { "job": 111582829330, "time": 197, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11320444964" }, { "job": 111582829287, "time": 184, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11321736376" }, { "job": 111582829332, "time": 237, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11322190451" }, { "job": 111582095130, "time": 227, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11321895916" }, { "job": 111582829197, "time": 105, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11321591512" }, { "job": 111582829304, "time": 159, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11321755749" }, { "job": 111582829218, "time": 140, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11321695738" }, { "job": 111582829241, "time": 164, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11322065297" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924", "_status": "success", "_upstream": "https://github.com/alexanderlynl/safestats", "_commit": { "id": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "author": "AlexanderLyNL ", "committer": "AlexanderLyNL ", "message": "cran-comment fix\n", "time": 1791154374 }, "_maintainer": { "name": "Alexander Ly", "email": "alexander.ly.nl@gmail.com", "login": "alexanderlynl", "description": "", "uuid": 10271675 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.5", "role": "Depends" }, { "package": "stats", "version": ">= 3.6", "role": "Imports" }, { "package": "lamW", "version": ">= 2.2.1", "role": "Imports" }, { "package": "hypergeo", "version": ">= 1.2-13", "role": "Imports" }, { "package": "survival", "version": ">= 3.2-13", "role": "Imports" }, { "package": "BiasedUrn", "version": ">= 1.07", "role": "Imports" }, { "package": "boot", "version": ">= 1.3-28", "role": "Imports" }, { "package": "dplyr", "version": ">= 1.0.6", "role": "Imports" }, { "package": "purrr", "version": ">= 0.3.5", "role": "Imports" }, { "package": "rlang", "version": ">= 1.0.6", "role": "Imports" }, { "package": "Matrix", "version": ">= 1.7-3", "role": "Imports" }, { "package": "graphics", "version": ">= 4.2.2", "role": "Imports" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "knitr", "version": ">= 1.49", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" } ], "_owner": "alexanderlynl", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-36", "n": 5 }, { "week": "2026-40", "n": 2 } ], "_tags": [ { "name": "v0.8.8", "date": "2026-09-05" } ], "_topics": [ "evalues", "hacktoberfest", "safe-testing", "statistics" ], "_stars": 16, "_contributors": [ { "user": "alexanderlynl", "count": 93, "uuid": 10271675 }, { "user": "rosanneturner", "count": 23, "uuid": 54638455 }, { "user": "judithterschure", "count": 1, "uuid": 50576181 } ], "_userbio": { "uuid": 10271675, "type": "user", "name": "AlexanderLyNL", "followers": 10 }, "_downloads": { "count": 503, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/safestats" }, "_devurl": "https://github.com/alexanderlynl/safestats", "_searchresults": 50, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/safestats.html" ], "_homeurl": "https://github.com/alexanderlynl/safestats", "_realowner": "alexanderlynl", "_cranurl": true, "_releases": [ { "version": "0.8.6", "date": "2022-02-01" }, { "version": "0.8.7", "date": "2022-11-24" }, { "version": "0.8.8", "date": "2026-09-08" } ], "_exports": [ "addCite", "ceil", "checkDoubleArgumentsDesignObject", "compute1F1AllVersions", "computeBetaBatchSafeZ", "computeBetaBootstrapper", "computeBetaSafeT", "computeBetaSafeZ", "computeBootObj", "computeConfidenceBoundForLogOddsTwoProportions", "computeConfidenceBoundsForDifferenceTwoProportions", "computeConfidenceIntervalT", "computeConfidenceIntervalZ", "computeConjugateCredibleIntervalTwoSampleT", "computeLogrankBetaFrom", "computeLogrankNEvents", "computeLogrankZ", "computeMinEsBatchSafeT", "computeMinEsBatchSafeZ", "computeMinEsBatchSaviT", "computeMinEsBatchSaviZ", "computeNPlanBatchSafeT", "computeNPlanBatchSafeZ", "computeNPlanBootstrapper", "computeNPlanSafeT", "computeNPlanSafeZ", "computeNPlanSaviT", "computeNPlanSaviZ", "computePowerBootstrapper", "computePowerSaviT", "computePowerSaviZ", "computeStatsForLogrank", "computeZTSumStats", "conjugateBfTStat", "conjugateBfTStatOld", "constructSafeDesignObj", "constructSafeTestObj", "constructSampleStoppingTimesList", "constructSaviDesignObj", "constructSaviTestObj", "designFreqT", "designFreqZ", "designSafe1aHelper", "designSafe2Helper", "designSafeLogrank", "designSafeLogrank2WantBeta", "designSafeT", "designSafeT1aWantNPlan", "designSafeT2WantBeta", "designSafeT3bWantParameter", "designSafeT3WantEsMin", "designSafeTwoProportions", "designSafeZ", "designSafeZ1aWantNPlan", "designSafeZ2WantBeta", "designSafeZ3bWantParameter", "designSafeZ3WantEsMin", "designSavi1aHelper", "designSavi2Helper", "designSavi2x2", "designSaviLogrank", "designSaviLogrank2WantBeta", "designSaviT", "designSaviT1aWantNPlan", "designSaviT2WantPower", "designSaviT3bWantParameter", "designSaviT3WantEsMin", "designSaviTwoProportions", "designSaviZ", "designSaviZ1aWantNPlan", "designSaviZ2WantPower", "designSaviZ3bWantParameter", "designSaviZ3WantEsMin", "generateNormalData", "generateSurvData", "isTryError", "lcosh", "logrankSingleEExact", "logrankSingleZ", "makeRunningIntersection", "matchAlphaRelevanceWith", "matchEParameterWith", "matchEsMinWith", "matchPowerWith", "matchRelevanceParameterWith", "plotConfidenceSequenceTwoProportions", "plotHistogramDistributionStoppingTimes", "pValueFromZStat", "pValueZTest", "returnOne", "rLogrank", "safe.prop.test", "safe.t.test", "safe.z.test", "safeLogrankTest", "safeLogrankTestStat", "safeTTest", "safeTTest.default", "safeTTest.formula", "safeTTestStat", "safeTTestStatNEffNu", "safeTTestStatNEffNuMom", "safeTTestStatTDensity", "safeTwoProportionsTest", "safeZTest", "safeZTestStat", "sampleLogrankStoppingTimes", "sampleStoppingTimesSafeT", "sampleStoppingTimesSafeZ", "sampleStoppingTimesSaviT", "sampleStoppingTimesSaviZ", "savi.prop.test", "savi.t.test", "savi.z.test", "savi2x2TestStat", "saviAnovaOneB", "saviAnovaStat", "saviLogrankTest", "saviLogrankTestStat", "saviRelevanceTStatNEffNu", "saviRelevanceZStat", "saviTTest", "saviTTestStat", "saviTTestStatNEffNu", "saviTTestStatNEffNuGrow", "saviTTestStatNEffNuMom", "saviTwoProportionsTest", "saviZTest", "saviZTestStat", "selectivelyContinueZOrTTestData", "setLowAndHighEsTrueZ", "setSafeStatsPlotOptionsAndReturnOldOnes", "simulateCoverageDifferenceTwoProportions", "simulateIncorrectStoppingTimesFisher", "simulateOptionalStoppingScenarioTwoProportions", "simulateTwoProportions", "subjectiveBfZStat", "tTestWidthDerivative", "zMarg" ], "_help": [ { "page": "addCite", "title": "Add a savi reference", "topics": [ "addCite" ] }, { "page": "ceil", "title": "A ceiling function with a tolerance at the 13th digit", "topics": [ "ceil" ] }, { "page": "checkAndReturnEsMinParameterSide", "title": "Checks consistency between the sided of the hypothesis and the minimal clinically relevant effect size or savi test defining parameter. Throws an error if the one-sided hypothesis is incongruent with the", "topics": [ "checkAndReturnEsMinParameterSide" ] }, { "page": "checkAndReturnNPlan", "title": "Check consistency between nPlan and the testType for one and two-sample z and t-tests", "topics": [ "checkAndReturnNPlan" ] }, { "page": "checkAndReturnsEsMinParameterSide", "title": "Checks consistency between the sided of the hypothesis and the minimal clinically relevant effect size or safe test defining parameter. Throws an error if the one-sided hypothesis is incongruent with the", "topics": [ "checkAndReturnsEsMinParameterSide" ] }, { "page": "checkDoubleArgumentsDesignObject", "title": "Helper function to check whether arguments are specified in a function at a higher level and already provided in the design object.", "topics": [ "checkDoubleArgumentsDesignObject" ] }, { "page": "compute1F1AllVersions", "title": "Computes 6 equivalent forms of the confluent hypergeometric function 1f1", "topics": [ "compute1F1AllVersions" ] }, { "page": "computeBetaBatchSaviZ", "title": "Helper function: Computes 1-power based on meanDiffTrue and nPlan", "topics": [ "computeBetaBatchSafeZ", "computeBetaBatchSaviZ" ] }, { "page": "computeBetaBootstrapper", "title": "Helper function to compute uncertainty regarding nPlan estimates", "topics": [ "computeBetaBootstrapper" ] }, { "page": "computePowerSaviT", "title": "Helper function: Computes the power of the saviTTest based on deltaMin and nPlan", "topics": [ "computeBetaSafeT", "computePowerSaviT" ] }, { "page": "computePowerSaviZ", "title": "Helper function: Computes the power based on meanDiffTrue and nPlan", "topics": [ "computeBetaSafeZ", "computePowerSaviZ" ] }, { "page": "computeBootObj", "title": "Computes the bootObj for sequential sampling procedures regarding nPlan, beta, the implied target", "topics": [ "computeBootObj" ] }, { "page": "computeConfidenceBoundForLogOddsTwoProportions", "title": "Estimate an upper or lower bound for a savi confidence sequence on the logarithm of the odds ratio for two proportions.", "topics": [ "computeConfidenceBoundForLogOddsTwoProportions" ] }, { "page": "computeConfidenceBoundsForDifferenceTwoProportions", "title": "Estimate Lower and Upper Bounds on the Confidence Sequence (Interval) for the Difference Divergence Measure for Two Proportions", "topics": [ "computeConfidenceBoundsForDifferenceTwoProportions" ] }, { "page": "computeConfidenceInterval2x2LogOdds", "title": "Helper function: Computes the savi confidence interval for logOdds", "topics": [ "computeConfidenceInterval2x2LogOdds" ] }, { "page": "computeConfidenceInterval2x2PropDiff", "title": "Helper function: Computes the savi confidence interval for propDiff", "topics": [ "computeConfidenceInterval2x2PropDiff" ] }, { "page": "computeConfidenceIntervalT", "title": "Helper function: Computes the savi confidence sequence for the mean in a T-test", "topics": [ "computeConfidenceIntervalT" ] }, { "page": "computeConfidenceIntervalZ", "title": "Helper function: Computes the savi confidence sequence for a Z-test", "topics": [ "computeConfidenceIntervalZ" ] }, { "page": "computeConfidenceSequence2x2LogOdds", "title": "Helper function: Computes the savi confidence sequence for logOdds", "topics": [ "computeConfidenceSequence2x2LogOdds" ] }, { "page": "computeConfidenceSequence2x2PropDiff", "title": "Helper function: Computes the savi confidence sequence for propDiff", "topics": [ "computeConfidenceSequence2x2PropDiff" ] }, { "page": "computeConjugateCredibleIntervalTwoSampleT", "title": "Computes the credible interval of a two-sample t-test based on conjugate priors", "topics": [ "computeConjugateCredibleIntervalTwoSampleT" ] }, { "page": "computeEsMinSavi2x2", "title": "Computes the smallest detectable propDiffMin with power probability, for the provided number of blocks", "topics": [ "computeEsMinSavi2x2" ] }, { "page": "computeLogrankBetaFrom", "title": "Helper function: Computes the type II error under optional stopping based on the minimal clinically relevant hazard ratio and the maximum number of nEvents.", "topics": [ "computeLogrankBetaFrom" ] }, { "page": "computeLogrankNEvents", "title": "Helper function: Computes the planned sample size based on the minimal clinical relevant hazard ratio, alpha and beta under optional stopping.", "topics": [ "computeLogrankNEvents" ] }, { "page": "computeLogrankZ", "title": "Helper function to computes the logrank statistic for 'Surv' objects of type \"right\" and \"counting\" with the hypergeometric variance.", "topics": [ "computeLogrankZ" ] }, { "page": "computeMinEsBatchSaviZ", "title": "Computes the meanDiffMin that is detectable with probability \"power\" for given nPlan", "topics": [ "computeMinEsBatchSafeZ", "computeMinEsBatchSaviZ" ] }, { "page": "computeMinEsBatchSaviT", "title": "Computes the smallest detectable deltaMin with power probability, for the provided sample size", "topics": [ "computeMinEsBatchSaviT" ] }, { "page": "computeNEff", "title": "Help function to compute the effective sample size based on a length 2 vector of samples", "topics": [ "computeNEff" ] }, { "page": "computeNPlanBatchSaviZ", "title": "Helper function: Computes nPlan based on meanDiffTrue, alpha and power.", "topics": [ "computeNPlanBatchSafeZ", "computeNPlanBatchSaviZ" ] }, { "page": "computeNPlanBatchSaviT", "title": "Helper function: Computes the planned sample size for the savi T-test based deltaMin, alpha and power", "topics": [ "computeNPlanBatchSaviT" ] }, { "page": "computeNPlanBootstrapper", "title": "Helper function to compute uncertainty regarding nPlan estimates", "topics": [ "computeNPlanBootstrapper" ] }, { "page": "computeNPlanSaviT", "title": "Helper function: Computes nPlan based on deltaMin and power", "topics": [ "computeNPlanSafeT", "computeNPlanSaviT" ] }, { "page": "computeNPlanSaviZ", "title": "Helper function: Computes nPlan based on meanDiffTrue, alpha and power", "topics": [ "computeNPlanSafeZ", "computeNPlanSaviZ" ] }, { "page": "computeNPlanSavi2x2", "title": "Helper function: Computes nBlocksPlan based on propDiffMin, alpha and power", "topics": [ "computeNPlanSavi2x2" ] }, { "page": "computePowerBootstrapper", "title": "Helper function to compute uncertainty regarding nPlan estimates", "topics": [ "computePowerBootstrapper" ] }, { "page": "computePowerSavi2x2", "title": "Helper function: Computes the power of the savi 2x2 test based on propDiffMin and nBlocks", "topics": [ "computePowerSavi2x2" ] }, { "page": "computeStatsForLogrank", "title": "Computes the sufficient statistics needed to compute 'logrankSingleZ'", "topics": [ "computeStatsForLogrank" ] }, { "page": "computeZTSumStats", "title": "Helper function to compute the relevant summary statistics in z and t-tests", "topics": [ "computeZTSumStats" ] }, { "page": "conjugateBfTStat", "title": "A \"subjective\" Bayes factor for the two-sample T-test", "topics": [ "conjugateBfTStat" ] }, { "page": "conjugateBfTStatOld", "title": "A \"subjective\" Bayes factor for the two-sample T-test", "topics": [ "conjugateBfTStatOld" ] }, { "page": "constructSaviDesignObj", "title": "Construct a savi design object to be set in the design function", "topics": [ "constructSafeDesignObj", "constructSaviDesignObj" ] }, { "page": "constructSaviTestObj", "title": "Construct a savi test object to be set in the savi testing function", "topics": [ "constructSafeTestObj", "constructSaviTestObj" ] }, { "page": "constructSampleStoppingTimesList", "title": "Construct a list to be set in the sampleStoppingTimes... function", "topics": [ "constructSampleStoppingTimesList" ] }, { "page": "defineTTestN", "title": "Computes a Sequence of (Effective) Sample Sizes of Z- and T-Tests", "topics": [ "defineTTestN" ] }, { "page": "designFreqT", "title": "Design a Frequentist T-Test", "topics": [ "designFreqT" ] }, { "page": "designFreqZ", "title": "Design a Frequentist Z-Test", "topics": [ "designFreqZ" ] }, { "page": "designSavi1aHelper", "title": "Helper function that extract the results for the design scenario 1a: Target nPlan", "topics": [ "designSafe1aHelper", "designSavi1aHelper" ] }, { "page": "designSavi2Helper", "title": "Helper function that extract the results for the design scenario 1a: Target nPlan", "topics": [ "designSafe2Helper", "designSavi2Helper" ] }, { "page": "designSaviLogrank", "title": "Designs a Safe Anytime-Valid Logrank Test Experiment", "topics": [ "designSafeLogrank", "designSaviLogrank" ] }, { "page": "designSaviLogrank2WantBeta", "title": "Helper function to design a savi logrank test (output beta)", "topics": [ "designSafeLogrank2WantBeta", "designSaviLogrank2WantBeta" ] }, { "page": "designSaviT", "title": "Design a Safe Anytime-Valid Experiment to Test Means with a Z Test", "topics": [ "computeMinEsBatchSafeT", "computeNPlanBatchSafeT", "designSafeT", "designSafeT2WantBeta", "designSafeT3bWantParameter", "designSafeT3WantEsMin", "designSaviT" ] }, { "page": "designSaviT1aWantNPlan", "title": "Helper function to designing a savi T-test (output nPlan)", "topics": [ "designSafeT1aWantNPlan", "designSaviT1aWantNPlan" ] }, { "page": "designSaviTwoProportions", "title": "Designs a Savi Experiment to Test Two Proportions in Stream Data", "topics": [ "designSafeTwoProportions", "designSaviTwoProportions" ] }, { "page": "designSaviZ", "title": "Design a Safe Anytime-Valid Experiment to Test Means with a Z Test", "topics": [ "designSafeZ", "designSaviZ" ] }, { "page": "designSaviZ1aWantNPlan", "title": "Helper function to designing a savi Z-test (output nPlan)", "topics": [ "designSafeZ1aWantNPlan", "designSaviZ1aWantNPlan" ] }, { "page": "designSaviZ2WantPower", "title": "Helper function to designing a Z-test (output power)", "topics": [ "designSafeZ2WantBeta", "designSaviZ2WantPower" ] }, { "page": "designSaviZ3bWantParameter", "title": "Helper function to designing a Z-test (output meanDiffMin based on the shortest interval at nPlan)", "topics": [ "designSafeZ3bWantParameter", "designSaviZ3bWantParameter" ] }, { "page": "designSaviZ3WantEsMin", "title": "Helper function to designing a Z-test (output esMin)", "topics": [ "designSafeZ3WantEsMin", "designSaviZ3WantEsMin" ] }, { "page": "designSavi2x2", "title": "Design a Safe Anytime-Valid Experiment to Test Two Proportions", "topics": [ "designSavi2x2" ] }, { "page": "designSaviT2WantPower", "title": "Helper function to designing a savi T-test (output power)", "topics": [ "designSaviT2WantPower" ] }, { "page": "designSaviT3bWantParameter", "title": "Helper function to designing a savi T-test (output deltaMin based on the shortest interval at nPlan)", "topics": [ "designSaviT3bWantParameter" ] }, { "page": "designSaviT3WantEsMin", "title": "Helper function to designing a Savi T-test (output esMin)", "topics": [ "designSaviT3WantEsMin" ] }, { "page": "extractNameFromArgs", "title": "Helper function: Get all names as entered by the user", "topics": [ "extractNameFromArgs" ] }, { "page": "fnchLogPartition", "title": "Log partition function of Fisher's noncentral hypergeometric distribution", "topics": [ "fnchLogPartition" ] }, { "page": "generateNormalData", "title": "Generates Normally Distributed Data Depending on the Design", "topics": [ "generateNormalData" ] }, { "page": "generateSurvData", "title": "Generate Survival Data which Can Be Analysed With the 'survival' Package", "topics": [ "generateSurvData" ] }, { "page": "getArgs", "title": "Helper function: Get all arguments as entered by the user", "topics": [ "getArgs" ] }, { "page": "getNameAlternative", "title": "Gets the Label of the Alternative Hypothesis", "topics": [ "getNameAlternative" ] }, { "page": "getNameTestType", "title": "Gets the Label of the Test", "topics": [ "getNameTestType" ] }, { "page": "isTryError", "title": "Checks Whether a Vector of Object Inherits from the Class 'try-error'", "topics": [ "isTryError" ] }, { "page": "lcosh", "title": "Logarithmic hyperbolic cosine", "topics": [ "lcosh" ] }, { "page": "logEValueVec2x2LogOddsEGauss", "title": "Plain eGauss e-process for logOdds", "topics": [ "logEValueVec2x2LogOddsEGauss" ] }, { "page": "logEValueVec2x2LogOddsGrow", "title": "Plain grow e-process for logOdds", "topics": [ "logEValueVec2x2LogOddsGrow" ] }, { "page": "logEValueVec2x2PropDiffEBeta", "title": "Plain eBeta e-process for propDiff", "topics": [ "logEValueVec2x2PropDiffEBeta" ] }, { "page": "logEValueVec2x2PropDiffGrow", "title": "Plain grow e-process for propDiff", "topics": [ "logEValueVec2x2PropDiffGrow" ] }, { "page": "logLikelihoodFNCH", "title": "Conditional log likelihood of 2x2 tables at one logOdds", "topics": [ "logLikelihoodFNCH" ] }, { "page": "logrankSingleEExact", "title": "Helper function computes single component of the exact logrank e-value", "topics": [ "logrankSingleEExact" ] }, { "page": "logrankSingleZ", "title": "Helper function computes single component of the logrank statistic", "topics": [ "logrankSingleZ" ] }, { "page": "makeRunningIntersection", "title": "Helper function to create running intersections", "topics": [ "makeRunningIntersection" ] }, { "page": "matchAlphaRelevanceWith", "title": "Checks and outputs a threshold for a minimal efficacy analysis", "topics": [ "matchAlphaRelevanceWith" ] }, { "page": "matchEParameterWith", "title": "Match the parameter of a savi z or t-test", "topics": [ "matchEParameterWith" ] }, { "page": "matchEsMinWith", "title": "Match the meanDiffMin of a savi z-test", "topics": [ "matchEsMinWith" ] }, { "page": "matchPowerWith", "title": "Helper function to check whether the power or beta (redundant now) argument is given", "topics": [ "matchPowerWith" ] }, { "page": "matchRelevanceParameterWith", "title": "Match the parameter of a minimal efficacy savi z-test", "topics": [ "matchRelevanceParameterWith" ] }, { "page": "plot.savi2x2Sim", "title": "Plots Results of Simulations for Comparing Hyperparameters for Savi Tests of Two Proportions", "topics": [ "plot.safe2x2Sim", "plot.savi2x2Sim" ] }, { "page": "plot.saviDesign", "title": "Plots the saviDesign object for designs with sample paths", "topics": [ "plot.safeDesign", "plot.saviDesign" ] }, { "page": "plot.saviTest", "title": "Plots the saviTest object for sequential analyses", "topics": [ "plot.safeTest", "plot.saviTest" ] }, { "page": "plotConfidenceSequenceTwoProportions", "title": "Plot bounds of a savi confidence sequence of the difference or log odds ratio for two proportions against the number of data blocks in two data streams ya and yb.", "topics": [ "plotConfidenceSequenceTwoProportions" ] }, { "page": "plotHistogramDistributionStoppingTimes", "title": "Plots the Histogram of Stopping Times", "topics": [ "plotHistogramDistributionStoppingTimes" ] }, { "page": "predictiveThetas2x2", "title": "Predictive Beta posterior means of thetaA and thetaB", "topics": [ "predictiveThetas2x2" ] }, { "page": "print.savi2x2Sim", "title": "Prints Results of Simulations for Comparing Hyperparameters for Savi Tests of Two Proportions", "topics": [ "print.safe2x2Sim", "print.savi2x2Sim" ] }, { "page": "print.saviDesign", "title": "Print Method for Savi Test Objects", "topics": [ "print.safeDesign", "print.saviDesign" ] }, { "page": "print.saviTest", "title": "Print Method for Savi Test Objects", "topics": [ "print.safeTest", "print.saviTest" ] }, { "page": "pValueZTest", "title": "Computes the p-value for the Z-test", "topics": [ "pValueFromZStat", "pValueZTest" ] }, { "page": "returnOne", "title": "Auxiliary function for sampling of the logrank simulations to return the integer 1 event per time.", "topics": [ "returnOne" ] }, { "page": "rLogrank", "title": "Randomly samples from a logrank distribution", "topics": [ "rLogrank" ] }, { "page": "saviLogrankTest", "title": "Safe Anytime-Valid Logrank Test", "topics": [ "safeLogrankTest", "safeLogrankTestStat", "saviLogrankTest", "saviLogrankTestStat" ] }, { "page": "saviTTest", "title": "Safe Anytime-Valid Student's T-Test.", "topics": [ "safe.t.test", "safeTTest", "safeTTest.default", "safeTTest.formula", "safeTTestStat", "safeTTestStatNEffNu", "safeTTestStatNEffNuMom", "safeTTestStatTDensity", "savi.t.test", "saviTTest", "saviTTest.default", "saviTTest.formula" ] }, { "page": "saviTwoProportionsTest", "title": "Perform a Savi Test for Two Proportions with Stream Data", "topics": [ "safe.prop.test", "safeTwoProportionsTest", "savi.prop.test", "saviTwoProportionsTest" ] }, { "page": "saviZTest", "title": "Safe Anytime-Valid Z-Test", "topics": [ "safe.z.test", "safeZTest", "safeZTest.default", "safeZTest.formula", "savi.z.test", "saviZTest", "saviZTest.default", "saviZTest.formula" ] }, { "page": "saviZTestStat", "title": "Computes E-Values Based on the Z-Statistic", "topics": [ "safeZTestStat", "saviRelevanceZStat", "saviZTestStat" ] }, { "page": "sampleLogrankStoppingTimes", "title": "Simulate stopping times for the exact savi logrank test", "topics": [ "sampleLogrankStoppingTimes" ] }, { "page": "sampleStoppingTimesSaviT", "title": "Simulate stopping times for the savi T-test", "topics": [ "sampleStoppingTimesSafeT", "sampleStoppingTimesSaviT" ] }, { "page": "sampleStoppingTimesSaviZ", "title": "Simulate stopping times for the savi Z-test", "topics": [ "sampleStoppingTimesSafeZ", "sampleStoppingTimesSaviZ" ] }, { "page": "sampleStoppingTimesSavi2x2", "title": "Simulate stopping times for the savi 2x2 test", "topics": [ "sampleStoppingTimesSavi2x2" ] }, { "page": "savi2x2TestStat", "title": "Safe Anytime-Valid Test of Two Proportions", "topics": [ "savi2x2TestStat" ] }, { "page": "savi2x2TestStatUmp", "title": "UMP conditional e-value of one 2x2 table", "topics": [ "savi2x2TestStatUmp" ] }, { "page": "saviAnovaOneB", "title": "Safe Anytime-Valid One-Way Anova", "topics": [ "saviAnovaOneB" ] }, { "page": "saviAnovaStat", "title": "Safe Anytime-Valid One-Way Anova based on summary statistics", "topics": [ "saviAnovaStat" ] }, { "page": "saviTTestStat", "title": "Computes E-Values Based on the T-Statistic", "topics": [ "saviRelevanceTStatNEffNu", "saviTTestStat", "saviTTestStatNEffNu", "saviTTestStatNEffNuGrow", "saviTTestStatNEffNuMom", "saviTTestStatTDensity" ] }, { "page": "selectivelyContinueZOrTTestData", "title": "Helper function to demonstrate the selective continuation of paired z-tests", "topics": [ "selectivelyContinueZOrTTestData" ] }, { "page": "setLowAndHighEsTrueZ", "title": "Helper function to determine the lower and upper bound for the search space for standardised meanDiffMin", "topics": [ "setLowAndHighEsTrueZ" ] }, { "page": "setSafeStatsPlotOptionsAndReturnOldOnes", "title": "Sets 'safestats' Plot Options and Returns the Current Plot Options.", "topics": [ "setSafeStatsPlotOptionsAndReturnOldOnes" ] }, { "page": "simulateCoverageDifferenceTwoProportions", "title": "Simulate the coverage of a savi confidence sequence for differences between proportions for a given distribution and savi design.", "topics": [ "simulateCoverageDifferenceTwoProportions" ] }, { "page": "simulateIncorrectStoppingTimesFisher", "title": "Simulate incorrect optional stopping with fisher's exact test's p-value as the stopping rule.", "topics": [ "simulateIncorrectStoppingTimesFisher" ] }, { "page": "simulateOptionalStoppingScenarioTwoProportions", "title": "Simulate an optional stopping scenario according to a savi design for two proportions", "topics": [ "simulateOptionalStoppingScenarioTwoProportions" ] }, { "page": "simulateTwoProportions", "title": "Compare Different Hyperparameter Settings for Savi Tests of Two Proportions.", "topics": [ "simulateTwoProportions" ] }, { "page": "solveRIPr2x2PropDiff", "title": "Reverse information projection onto a fixed propDiff", "topics": [ "solveRIPr2x2PropDiff" ] }, { "page": "solveUmpLogOdds", "title": "Uniformly most powerful log odds ratio of a one-sided conditional test", "topics": [ "solveUmpLogOdds" ] }, { "page": "solveWorstCaseTheta2x2PropDiff", "title": "Worst-case baseline of the propDiff grow test", "topics": [ "solveWorstCaseTheta2x2PropDiff" ] }, { "page": "subjectiveBfZStat", "title": "A subjective Bayes factor for the two-sample Z-test", "topics": [ "subjectiveBfZStat" ] }, { "page": "tryOrFailWithNA", "title": "Tries to Evaluate an Expression and Fails with 'NA'", "topics": [ "tryOrFailWithNA" ] }, { "page": "tTestWidthDerivative", "title": "Internal function to solve the smallest width of an eGauss t-test", "topics": [ "tTestWidthDerivative" ] }, { "page": "zMarg", "title": "Logarithmic marginal likelihood of the normal with conjugate priors", "topics": [ "zMarg" ] } ], "_readme": "https://github.com/alexanderlynl/safestats/raw/HEAD/README.md", "_rundeps": [ "BiasedUrn", "boot", "cli", "contfrac", "deSolve", "dplyr", "elliptic", "generics", "glue", "hypergeo", "lamW", "lattice", "lifecycle", "magrittr", "MASS", "Matrix", "pillar", "pkgconfig", "purrr", "R6", "Rcpp", "RcppParallel", "rlang", "survival", "tibble", "tidyselect", "utf8", "vctrs", "withr" ], "_vignettes": [ { "source": "aInstallationGuide.Rmd", "filename": "aInstallationGuide.html", "title": "Installing the safestats package ", "author": "Alexander Ly, Rosanne Turner, Udo Boehm, Rianne de Heide, Peter Grunwald", "engine": "knitr::rmarkdown", "headings": [ "1. Installing the development version of the safestats package", "a. Install using the remotes package", "b. Install using a downloaded tar.gz file", "2. First example: Designing a savi z-test experiment", "A first example" ], "created": "2026-09-05 12:09:15", "modified": "2026-09-05 14:58:20", "commits": 2 }, { "source": "safestats-vignetteT.Rmd", "filename": "safestats-vignetteT.html", "title": "Flexible Safe Anytime-Valid Tests for Practical Scenarios", "author": "Alexander Ly, Udo Boehm and Rosanne Turner", "engine": "knitr::rmarkdown", "headings": [ "Installation", "1. Designing savi t-test experiments", "Type I error and power", "Case (I): Designing experiments where the minimal clinically relevant effect size and the targeted power are known. Target: The sample size to plan for", "Case (II): Minimal clinically relevant effect size and a budget constrained number of samples known. Target: Power", "Case (III): A desirable power and a budget constrained number of samples known. Target: Detectable effect size.", "2. Inference with savi tests: Optional stopping", "Savi tests conserve the type I error rate: Batch analysis", "Savi tests allow for early stopping without inflating the type I error rate above the tolerable $\\alpha$-level", "Optional stopping is problematic for p-values", "Optional stopping does not cause savi tests to over-reject the null", "Savi tests detect the effect early if it is present: deltaTrue equal to deltaMin", "Savi tests detect the effect even earlier if deltaTrue is larger than deltaMin", "3. Optional Continuation", "Optional continuation is problematic for p-values and leads to overinflating the type I error rate", "i. Optional continuation by extending the experiment does not result in savi tests exceeding the tolerable $\\alpha$-level", "When the effect is present optional continuation results in savi tests correctly rejecting the null", "4. Optional contination and meta-analysis: Extending the research endeavours through replication studies", "Type I error is guaranteed when multiplying e-values", "Meta-analysis e-values under the alternative", "Conclusion" ], "created": "2026-09-05 12:09:15", "modified": "2026-10-04 22:45:04", "commits": 4 }, { "source": "ingka1Testing.Rmd", "filename": "ingka1Testing.html", "title": "I. Testing: P-values and e-variables", "author": "Alexander Ly, Rosanne Turner, Udo Boehm, Rianne de Heide, Peter Grunwald", "engine": "knitr::rmarkdown", "headings": [ "The two-sample z-test", "1. Sequential use of p-values over-inflates the type I error", "Sequential analysis", "One sample path", "The behaviour of the sequential p-value procedure under multiple/repeated use", "2. Sequential use of a savi test/e-variable will not over-inflate the type I error", "The behaviour of the e-variable procedure under multiple/repeated use", "Concluding remarks" ], "created": "2026-09-05 12:09:15", "modified": "2026-09-05 12:09:15", "commits": 1 }, { "source": "bTesting.Rmd", "filename": "bTesting.html", "title": "I. Testing: P-values, subjective Bayes factor, and e-variables", "author": "Alexander Ly, Rosanne Turner, Udo Boehm, Rianne de Heide, Peter Grunwald", "engine": "knitr::rmarkdown", "headings": [ "The two-sample z-test", "1. Sequential use of p-values over-inflates the type I error", "Sequential analysis", "One sample path", "The behaviour of the sequential p-value procedure under multiple/repeated use", "2. Sequential use of Bayes factors based on subjectively chosen priors can also over-inflate the type I error", "The behaviour of the subjective Bayes factor procedure under multiple/repeated use", "3. Sequential use of a savi test/e-variable will not over-inflate the type I error", "The behaviour of the e-variable procedure under multiple/repeated use", "Concluding remarks" ], "created": "2026-09-05 12:09:15", "modified": "2026-09-05 12:09:15", "commits": 1 }, { "source": "cDesign.Rmd", "filename": "cDesign.html", "title": "II. Design of experiments: Behaviour of e-variables under alternatives", "author": "Alexander Ly, Rosanne Turner, Udo Boehm, Rianne de Heide, Peter Grunwald", "engine": "knitr::rmarkdown", "headings": [ "1. Designing savi z-test experiments", "One sample path", "Early stopping: True effect size equals the minimal clinical relevant mean effect size", "Even earlier stopping: True effect size larger than the minimal clinical relevant mean effect size", "Optional continuation: True effect size smaller than the minimal clinical relevant mean effect size", "Meta-analysis e-values: Combining the evidence across studies by multiplication", "Concluding remarks" ], "created": "2026-09-05 12:09:15", "modified": "2026-09-05 12:09:15", "commits": 1 }, { "source": "ingka2ConfidenceSequences.Rmd", "filename": "ingka2ConfidenceSequences.html", "title": "II. Interval estimation: Classical confidence intervals and anytime-valid confidence sequences", "author": "Alexander Ly, Rosanne Turner, Udo Boehm, Rianne de Heide, Peter Grunwald", "engine": "knitr::rmarkdown", "headings": [ "Interval estimation for a normal mean", "1. Classical 95% confidence intervals fail to cover the true mean with 95% chance across time", "One sample path", "The behaviour of classical confidence intervals across time under multiple use", "2. The 95% anytime-valid confidence sequence/intervals will always cover the true mean with at least 95% chance", "The behaviour of anytime-valid confidence sequences across time under multiple use", "Sensitivity wrt to the parameter gMom: Width of the confidence intervals versus anytime-valid confidence intervals" ], "created": "2026-09-05 12:09:15", "modified": "2026-09-05 12:09:15", "commits": 1 }, { "source": "ingka3Design.Rmd", "filename": "ingka3Design.html", "title": "III. Design of experiments: Behaviour of e-variables under alternatives", "author": "Alexander Ly, Rosanne Turner, Udo Boehm, Rianne de Heide, Peter Grunwald", "engine": "knitr::rmarkdown", "headings": [ "1. Designing safe z-test experiments", "One sample path", "Early stopping: True effect size equals the minimal clinical relevant mean effect size", "Even earlier stopping: True effect size larger than the minimal clinical relevant mean effect size", "Optional continuation: True effect size smaller than the minimal clinical relevant mean effect size", "Meta-analysis e-values: Combining the evidence across studies by multiplication", "Concluding remarks" ], "created": "2026-09-05 12:09:15", "modified": "2026-09-05 12:09:15", "commits": 1 }, { "source": "dConfidenceSequences.Rmd", "filename": "dConfidenceSequences.html", "title": "III. Interval estimation: Classical confidence intervals, (Bayesian) credible interval, and anytime-valid confidence sequences", "author": "Alexander Ly, Rosanne Turner, Udo Boehm, Rianne de Heide, Peter Grunwald", "engine": "knitr::rmarkdown", "headings": [ "Interval estimation for a normal mean", "1. Classical 95% confidence intervals fail to cover the true mean with 95% chance across time", "One sample path", "The behaviour of classical confidence intervals across time under multiple use", "2. Bayesian 95% credible intervals fail to cover the true mean with 95% chance across time", "The behaviour of (Bayesian) credible intervals across time under multiple use", "3. The 95% anytime-valid confidence sequence/intervals will always cover the true mean with at least 95% chance", "The behaviour of anytime-valid confidence sequences across time under multiple use", "Sensitivity wrt to the parameter g and gMom: Credible intervals versus anytime-valid confidence intervals" ], "created": "2026-09-05 12:09:15", "modified": "2026-09-05 12:09:15", "commits": 1 }, { "source": "contingency-tables-vignette.Rmd", "filename": "contingency-tables-vignette.html", "title": "Savi Tests and Confidence Intervals for Tests of Two Proportions: Practical Scenarios", "author": "Rosanne Turner, Alexander Ly and Peter Grünwald", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "1. Designing Savi Experiments", "Case (I): Designing experiments with the minimal clinically relevant effect size known", "Case (II): Minimal clinically relevant effect size unknown, but maximum number of samples known.", "Short examples of non-standard design settings", "Unequal group sizes", "Non-standard Beta priors", "Restricting the alternative hypothesis", "2. Inference with Savi Tests and Optional Stopping", "True effect size equals minimal clinically relevant effect size", "True effect size larger than the minimal clinically relevant effect size", "Data under the null: True effect size is zero, thus, much smaller than the minimal clinically relevant effect size", "Classical test \"Fisher's exact test\" under the null with optional stopping", "3. Optional Continuation for tests of two proportions", "4. Confidence intervals", "Confidence sequence for difference between success rates", "Confidence sequence for log of the odds ratio", "References" ], "created": "2022-01-06 16:18:06", "modified": "2026-09-05 12:09:15", "commits": 5 } ], "_score": 7.15836249209525, "_indexed": true, "_nocasepkg": "safestats", "_universes": [ "alexanderlynl" ], "_previous": "0.8.8", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.8.9", "date": "2026-10-05T01:44:44.000Z", "distro": "resolute", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/775bac7236cbe604b1d440a421e9a5329f10605b939e4d87b6fc6565fd5e8df2", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" }, { "r": "4.6.1", "os": "linux", "version": "0.8.9", "date": "2026-10-05T01:44:43.000Z", "distro": "resolute", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/0f8c5ac5aee0964fd0f932cab9a6330cf2ecdf86cbd4a16b75a7c62e521c8db3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" }, { "r": "4.5.3", "os": "mac", "version": "0.8.9", "date": "2026-10-05T01:44:42.000Z", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/1239e6d0393f7866246e0faafdc3cb9c99abd561545ea46040dfa01fd5406591", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" }, { "r": "4.6.1", "os": "mac", "version": "0.8.9", "date": "2026-10-05T01:44:55.000Z", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/492b8ec892a2bd8ec4da2b77d7451129ef385c079b544a53f2a471db44258198", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" }, { "r": "4.6.0", "os": "wasm", "version": "0.8.9", "date": "2026-10-05T01:44:30.000Z", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/5a84b8468688526e143416792f879581c79d3ffdf88f27da44f115df38e37f9e", "status": "success", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" }, { "r": "4.7.0", "os": "win", "version": "0.8.9", "date": "2026-10-05T01:43:43.000Z", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/d1cac4f335cb3387524b172d0f7064a91acc8e91313e1296f8670b9f15d7be9a", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" }, { "r": "4.5.3", "os": "win", "version": "0.8.9", "date": "2026-10-05T01:43:52.000Z", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/dc1f640774ea1866c47bf30a05518db89b2a57781ae2839b3ee5be8a9ed78520", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" }, { "r": "4.6.1", "os": "win", "version": "0.8.9", "date": "2026-10-05T01:43:45.000Z", "commit": "1079515398a0fe4d235bfca8f135ce4d4a3f95e2", "fileid": "https://r2.ropensci.org/2372b54367ff07d98ec9108e750b2199931b97ee5316749bf9efccf659c5a7cc", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/alexanderlynl/actions/runs/37252225924" } ] }