{"title":"edibble: An R package to encapsulate elements of experimental designs for better planning, management and workflow","authors":"Emi Tanaka","doi":"arxiv-2311.09705","DOIUrl":null,"url":null,"abstract":"I present an R package called edibble that facilitates the design of\nexperiments by encapsulating elements of the experiment in a series of\ncomposable functions. This package is an interpretation of \"the grammar of\nexperimental designs\" by Tanaka (2023) in the R programming language. The main\nfeatures of the edibble package are demonstrated, illustrating how it can be\nused to create a wide array of experimental designs. The implemented system\naims to encourage cognitive thinking for holistic planning and data management\nof experiments in a streamlined workflow. This workflow can increase the\ninherent value of experimental data by reducing potential errors or noise with\ncareful preplanning, as well as, ensuring fit-for-purpose analysis of\nexperimental data.","PeriodicalId":501323,"journal":{"name":"arXiv - STAT - Other Statistics","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Other Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.09705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
I present an R package called edibble that facilitates the design of
experiments by encapsulating elements of the experiment in a series of
composable functions. This package is an interpretation of "the grammar of
experimental designs" by Tanaka (2023) in the R programming language. The main
features of the edibble package are demonstrated, illustrating how it can be
used to create a wide array of experimental designs. The implemented system
aims to encourage cognitive thinking for holistic planning and data management
of experiments in a streamlined workflow. This workflow can increase the
inherent value of experimental data by reducing potential errors or noise with
careful preplanning, as well as, ensuring fit-for-purpose analysis of
experimental data.