{
  "_id": "6a1d465e1d7bb097a0a42372",
  "Package": "prepdat",
  "Title": "Preparing Experimental Data for Statistical Analysis",
  "Version": "1.0.8",
  "Authors@R": "c(\nperson(\"Ayala S.\", \"Allon\", email = \"ayalaallon@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Roy\", \"Luria\", role = \"aut\"),\nperson(\"James\", \"Grange\", role = \"ctb\"),\nperson(\"Nachshon\", \"Meiran\", role = \"ctb\"))",
  "Description": "Prepares data for statistical analysis (e.g., analysis of\nvariance ;ANOVA) by enabling the user to easily and quickly\nmerge (using the file_merge() function) raw data files into one\nmerged table and then aggregate the merged table (using the\nprep() function) into a finalized table while keeping track and\nsummarizing every step of the preparation. The finalized table\ncontains several possibilities for dependent measures of the\ndependent variable. Most suitable when measuring variables in\nan interval or ratio scale (e.g., reaction-times) and/or\ndiscrete values such as accuracy. Main functions included are\nfile_merge() and prep(). The file_merge() function vertically\nmerges individual data files (in a long format) in which each\nline is a single observation to one single dataset. The prep()\nfunction aggregates the single dataset according to any\ncombination of grouping variables (i.e., between-subjects and\nwithin-subjects independent variables, respectively), and\nreturns a data frame with a number of dependent measures for\nfurther analysis for each cell according to the combination of\nprovided grouping variables. Dependent measures for each cell\ninclude among others means before and after rejecting all\nvalues according to a flexible standard deviation criteria,\nnumber of rejected values according to the flexible standard\ndeviation criteria, proportions of rejected values according to\nthe flexible standard deviation criteria, number of values\nbefore rejection, means after rejecting values according to\nprocedures described in Van Selst & Jolicoeur (1994; suitable\nwhen measuring reaction-times), standard deviations, medians,\nmeans according to any percentile (e.g., 0.05, 0.25, 0.75,\n0.95) and harmonic means. The data frame prep() returns can\nalso be exported as a txt file to be used for statistical\nanalysis in other statistical programs.",
  "License": "GPL-3",
  "LazyData": "true",
  "URL": "http://github.com/ayalaallon/prepdat",
  "BugReports": "http://github.com/ayalaallon/prepdat/issues",
  "RoxygenNote": "5.0.1",
  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://ayalaallon.r-universe.dev",
  "Date/Publication": "2019-03-01 01:42:05 UTC",
  "RemoteUrl": "https://github.com/ayalaallon/prepdat",
  "RemoteRef": "HEAD",
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  "Packaged": {
    "Date": "2026-06-01 08:40:19 UTC",
    "User": "root"
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  "Author": "Ayala S. Allon [aut, cre],\nRoy Luria [aut],\nJames Grange [ctb],\nNachshon Meiran [ctb]",
  "Maintainer": "Ayala S. Allon <ayalaallon@gmail.com>",
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  "_published": "2026-06-01T08:44:14.388Z",
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    "author": "Ayala Allon <ayalaallon@users.noreply.github.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Update README.md",
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