{ "_id": "6a1d76f31d7bb097a0a51d35", "Package": "testassay", "Type": "Package", "Title": "A Hypothesis Testing Framework for Validating an Assay for\nPrecision", "Version": "0.1.1", "Author": "Michael C Sachs and Michael P Fay", "Maintainer": "Michael C Sachs ", "Description": "A common way of validating a biological assay for is\nthrough a procedure, where m levels of an analyte are measured\nwith n replicates at each level, and if all m estimates of the\ncoefficient of variation (CV) are less than some prespecified\nlevel, then the assay is declared validated for precision\nwithin the range of the m analyte levels. Two limitations of\nthis procedure are: there is no clear statistical statement of\nprecision upon passing, and it is unclear how to modify the\nprocedure for assays with constant standard deviation. We\nprovide tools to convert such a procedure into a set of m\nhypothesis tests. This reframing motivates the m:n:q procedure,\nwhich upon completion delivers a 100q% upper confidence limit\non the CV. Additionally, for a post-validation assay output of\ny, the method gives an ``effective standard deviation\ninterval'' of log(y) plus or minus r, which is a 68% confidence\ninterval on log(mu), where mu is the expected value of the\nassay output for that sample. Further, the m:n:q procedure can\nbe straightforwardly applied to constant standard deviation\nassays. We illustrate these tools by applying them to a growth\ninhibition assay. This is an implementation of the methods\ndescribed in Fay, Sachs, and Miura (2018)\n.", "License": "MIT + file LICENSE", "LazyData": "TRUE", "VignetteBuilder": "knitr", "RoxygenNote": "7.1.0", "Repository": "https://sachsmc.r-universe.dev", "Date/Publication": "2020-06-03 13:04:23 UTC", "RemoteUrl": "https://github.com/sachsmc/testassay", "RemoteRef": "HEAD", "RemoteSha": "2dd44ce296bff8d0ce20022e1aab5593eac2cbcd", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-01 12:08:59 UTC", "User": "root" }, "MD5sum": "14edd85bef50ae5ea6dbc344ff53f607", "_user": "sachsmc", "_type": "src", "_file": "testassay_0.1.1.tar.gz", "_fileid": "81bc77a9b3c70e9db37bdd01a0eae843817bcff923ff2a311e5ec9938ae55773", "_filesize": 244852, "_sha256": "81bc77a9b3c70e9db37bdd01a0eae843817bcff923ff2a311e5ec9938ae55773", "_created": "2026-06-01T12:08:59.000Z", "_published": "2026-06-01T12:11:31.681Z", "_distro": "noble", "_jobs": [ { "job": 78848957715, "time": 114, "config": "linux-devel-x86_64", "r": 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"artifact": "7331075294" } ], "_buildurl": "https://github.com/r-universe/sachsmc/actions/runs/26753821327", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/sachsmc/testassay", "_commit": { "id": "2dd44ce296bff8d0ce20022e1aab5593eac2cbcd", "author": "Michael Sachs ", "committer": "Michael Sachs ", "message": "release\n", "time": 1591189463 }, "_maintainer": { "name": "Michael C Sachs", "email": "sachsmc@gmail.com", "login": "sachsmc", "linkedin": "in/michael-sachs-09324659", "description": "", "uuid": 5464185 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" } ], "_owner": "sachsmc", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_contributors": [ { "user": "sachsmc", "count": 15, "uuid": 5464185 } ], "_userbio": { "uuid": 5464185, "type": "user", "name": "Michael Sachs" }, "_downloads": { "count": 144, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/testassay" }, "_devurl": "https://github.com/sachsmc/testassay", "_searchresults": 6, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/testassay.html", "manual.pdf" ], "_homeurl": "https://github.com/sachsmc/testassay", "_realowner": "sachsmc", "_cranurl": true, "_releases": [ { "version": "0.1.0", "date": "2016-11-29" }, { "version": "0.1.1", "date": "2020-06-03" } ], "_exports": [ "lognormConstCVCI", "normConstCVCI", "testassay" ], "_datasets": [ { "name": "gia", "title": "Growth Inhibition Assay", "object": "gia", "class": [ "data.frame" ], "fields": [ "parasite", "assay", "elisa", "gia", "sample", "meanAAgia", "varAAgia" ], "rows": 52, "table": true, "tojson": true } ], "_help": [ { "page": "gia", "title": "Growth Inhibition Assay", "topics": [ "gia" ] }, { "page": "lognormConstCVCI", "title": "log-normal constant CV model", "topics": [ "lognormConstCVCI" ] }, { "page": "normConstCVCI", "title": "Log-centered confidence intervals from a Normal constant coeffficient of variation model", "topics": [ "normConstCVCI" ] }, { "page": "predict.assaytest", "title": "Construct effective standard deviation intervals for observed assay values", "topics": [ "predict.assaytest" ] }, { "page": "print.assaytest", "title": "Print the results of an assaytest", "topics": [ "print.assaytest" ] }, { "page": "testassay", "title": "Hypothesis testing procedure for assay validation for precision", "topics": [ "testassay" ] } ], "_readme": "https://github.com/sachsmc/testassay/raw/HEAD/README.md", "_rundeps": [], "_vignettes": [ { "source": "GIAValidationExample.Rmd", "filename": "GIAValidationExample.html", "title": "Validation of Growth Inhibition Assay using 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