{ "_id": "6aee4f6a482d117aebab634c", "Type": "Package", "Package": "see", "Title": "Model Visualisation Toolbox for 'easystats' and 'ggplot2'", "Version": "0.15.0.7", "Authors@R": "c(person(given = \"Daniel\",\nfamily = \"Lüdecke\",\nrole = c(\"aut\", \"cre\"),\nemail = \"officialeasystats@gmail.com\",\ncomment = c(ORCID = \"0000-0002-8895-3206\")),\nperson(given = \"Dominique\",\nfamily = \"Makowski\",\nrole = c(\"aut\", \"inv\"),\nemail = \"dom.makowski@gmail.com\",\ncomment = c(ORCID = \"0000-0001-5375-9967\")),\nperson(given = \"Indrajeet\",\nfamily = \"Patil\",\nrole = c(\"aut\"),\nemail = \"patilindrajeet.science@gmail.com\",\ncomment = c(ORCID = \"0000-0003-1995-6531\")),\nperson(given = \"Mattan S.\",\nfamily = \"Ben-Shachar\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"matanshm@post.bgu.ac.il\",\ncomment = c(ORCID = \"0000-0002-4287-4801\")),\nperson(given = \"Brenton M.\",\nfamily = \"Wiernik\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"brenton@wiernik.org\",\ncomment = c(ORCID = \"0000-0001-9560-6336\")),\nperson(given = \"Rémi\",\nfamily = \"Thériault\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"remi.theriault@mail.mcgill.ca\",\ncomment = c(ORCID = \"0000-0003-4315-6788\")),\nperson(given = \"Philip\",\nfamily = \"Waggoner\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"philip.waggoner@gmail.com\",\ncomment = c(ORCID = \"0000-0002-7825-7573\")),\nperson(given = \"Jeffrey R.\",\nfamily = \"Stevens\",\nrole = \"ctb\",\nemail = \"jeffrey.r.stevens@gmail.com\",\ncomment = c(ORCID = \"0000-0003-2375-1360\")),\nperson(given = \"Julius\",\nfamily = \"Bogomolovas\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0001-8344-1909\")),\nperson(given = \"Matthew\",\nfamily = \"Smith\",\nrole = \"rev\",\nemail = \"M.Smith3@napier.ac.uk\"),\nperson(given = \"Jakob\",\nfamily = \"Bossek\",\nrole = \"rev\",\nemail = \"bossek@wi.uni-muenster.de\"))", "Maintainer": "Daniel Lüdecke ", "Description": "Provides plotting utilities supporting packages in the\n'easystats' ecosystem\n() and some extra\nthemes, geoms, and scales for 'ggplot2'. Color scales are based\non . References: Lüdecke et al. (2021)\n.", "License": "MIT + file LICENSE", "URL": "https://easystats.github.io/see/", "BugReports": "https://github.com/easystats/see/issues", "Encoding": "UTF-8", "Language": "en-US", "Roxygen": "list(markdown = TRUE)", "Config/testthat/edition": "3", "Config/testthat/parallel": "false", "Config/Needs/website": "easystats/easystatstemplate", "Config/rcmdcheck/ignore-inconsequential-notes": "true", "Config/roxygen2/version": "8.1.1", "Repository": "https://easystats.r-universe.dev", "Date/Publication": "2026-11-03 12:19:34 UTC", "RemoteUrl": "https://github.com/easystats/see", "RemoteRef": "HEAD", "RemoteSha": "ae212b017a52d05805848e77b9a2a26408417243", "NeedsCompilation": "no", "Packaged": { "Date": "2026-11-06 21:44:16 UTC", "User": "root" }, "Author": "Daniel Lüdecke [aut, cre] (ORCID:\n),\nDominique Makowski [aut, inv] (ORCID:\n),\nIndrajeet Patil [aut] (ORCID: ),\nMattan S. Ben-Shachar [aut, ctb] (ORCID:\n),\nBrenton M. Wiernik [aut, ctb] (ORCID:\n),\nRémi Thériault [aut, ctb] (ORCID:\n),\nPhilip Waggoner [aut, ctb] (ORCID:\n),\nJeffrey R. Stevens [ctb] (ORCID:\n),\nJulius Bogomolovas [ctb] (ORCID:\n),\nMatthew Smith [rev],\nJakob Bossek [rev]", "_user": "easystats", "_type": "src", "_file": "see_0.15.0.7.tar.gz", "_fileid": "https://r2.ropensci.org/1e4c515e64f1fc116a1c958075f2af95aa776c903f4ac18bb515115e2b4eba11", "_filesize": 589879, "_sha256": "1e4c515e64f1fc116a1c958075f2af95aa776c903f4ac18bb515115e2b4eba11", "_expires": "2027-02-14T22:06:32.000Z", "_created": "2026-11-06T21:44:16.000Z", "_published": "2026-11-06T22:06:33.801Z", "_upstream": "https://github.com/easystats/see", "_status": "success", "_maintainer": { "name": "Daniel Lüdecke", "email": "officialeasystats@gmail.com", "orcid": "0000-0002-8895-3206" }, "_jobs": [ { "job": 128172359518, "time": 384, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13544201155" }, { "job": 128172359702, "time": 562, "config": "linux-release-x86_64", "r": "4.6.2", "check": "OK", "artifact": "13544061357" }, { "job": 128172359499, "time": 300, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "13545025235" }, { "job": 128172359420, "time": 397, "config": "macos-release-arm64", "r": "4.6.2", "check": "OK", "artifact": "13543623986" }, { "job": 128169585875, "time": 362, "config": "source", "r": "4.6.2", "check": "OK", "artifact": "13543725387" }, { "job": 128172359336, "time": 151, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "13544180357" }, { "job": 128172359481, "time": 312, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13543167716" }, { "job": 128172359547, "time": 371, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "13544325809" }, { "job": 128172359678, "time": 336, "config": "windows-release-x86_64", "r": "4.6.2", "check": "OK", "artifact": "13542769616" } ], "_buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518", "_commit": { "id": "ae212b017a52d05805848e77b9a2a26408417243", "author": "Jeffrey Girard ", "committer": "GitHub ", "message": "Match emmeans contrast labels to the means in lighthouse plots (#497)\n\nWith `backend = \"emmeans\"`, the contrast levels aren't labeled the way\nthe means are. emmeans adds the variable name when all levels of a\nvariable look like numbers (`cyl6`, while the means hold `6`), puts\nparentheses around labels with an operator (`(neg-1)`), and joins the\nlevels of a joint contrast with a space (`auto cyl6`, where the plot\nexpects `auto, 6`). The lighthouse plot then finds no means row for\nthese levels, so it draws no beams and warns that the means have no row\nfor them. Joint contrasts of word levels fail the same way.\n\nThis PR maps the emmeans labels to the labels of the means before the\nplot matches them. It applies only to contrasts from the emmeans\nbackend. A label that fits two combinations of levels, such as `a b c`\nfor `a b` and `c` or for `a` and `b c`, stays as it is, so that contrast\nisn't drawn and the warning stays.\n\nThe new test compares each case with the same model fitted with word\nlevels. On main, number-like levels, negative levels and joint contrasts\ndraw no beams. With the fix, they get the same beams as word levels.\n\nI compared plots from main and from this branch for one variable with 2,\n3 and 4 levels, negative and decimal levels, `by`, joint contrasts of 2\nand 3 variables, `show_data = TRUE`, a logit model and a log response.\nWord levels, and number-like levels that appear only in the `by` panels,\nlook the same as on main.\n\nThe plots this brings back show that lighthouse plots get crowded\nquickly. There's one beam per pair of levels, so 4 levels give 6 beams\nand a joint contrast of 6 combinations gives 15. This PR doesn't change\nthat, and I'll open a separate issue about it.\n\n---------\n\nCo-authored-by: Daniel ", "time": 1793708374 }, "_distro": "resolute", "_host": "GitHub-Actions", "_registered": true, "_dependencies": [ { "package": "graphics", "role": "Depends" }, { "package": "grDevices", "role": "Depends" }, { "package": "R", "version": ">= 4.1", "role": "Depends" }, { "package": "stats", "role": "Depends" }, { "package": "bayestestR", "version": ">= 0.19.0", "role": "Imports" }, { "package": "correlation", "version": ">= 0.8.8", "role": "Imports" }, { "package": "datawizard", "version": ">= 1.4.0", "role": "Imports" }, { "package": "effectsize", "version": ">= 1.0.3", "role": "Imports" }, { "package": "ggplot2", "version": ">= 4.0.3", "role": "Imports" }, { "package": "insight", "version": ">= 1.5.4", "role": "Imports" }, { "package": "modelbased", "version": ">= 0.17.0", "role": "Imports" }, { "package": "patchwork", "version": ">= 1.3.2", "role": "Imports" }, { "package": "parameters", "version": ">= 0.29.3", "role": "Imports" }, { "package": "performance", "version": ">= 0.18.2", "role": "Imports" }, { "package": "BH", "role": "Suggests" }, { "package": "brms", "role": "Suggests" }, { "package": "collapse", "role": "Suggests" }, { "package": "curl", "role": "Suggests" }, { "package": "DHARMa", "role": "Suggests" }, { "package": "discovr", "role": "Suggests" }, { "package": "emmeans", "role": "Suggests" }, { "package": "factoextra", "role": "Suggests" }, { "package": "Formula", "role": "Suggests" }, { "package": "ggdag", "role": "Suggests" }, { "package": "ggdist", "role": "Suggests" }, { "package": "ggraph", "role": "Suggests" }, { "package": "ggrepel", "role": "Suggests" }, { "package": "ggridges", "role": "Suggests" }, { "package": "ggside", "role": "Suggests" }, { "package": "glmmTMB", "role": "Suggests" }, { "package": "grid", "role": "Suggests" }, { "package": "httr2", "role": "Suggests" }, { "package": "lavaan", "role": "Suggests" }, { "package": "lme4", "role": "Suggests" }, { "package": "logspline", "role": "Suggests" }, { "package": "marginaleffects", "role": "Suggests" }, { "package": "MASS", "role": "Suggests" }, { "package": "mclogit", "role": "Suggests" }, { "package": "mclust", "role": "Suggests" }, { "package": "merDeriv", "role": "Suggests" }, { "package": "mgcv", "role": "Suggests" }, { "package": "metafor", "role": "Suggests" }, { "package": "NbClust", "role": "Suggests" }, { "package": "nFactors", "role": "Suggests" }, { "package": "psych", "role": "Suggests" }, { "package": "qqplotr", "version": ">= 0.0.6", "role": "Suggests" }, { "package": "randomForest", "role": "Suggests" }, { "package": "RcppEigen", "role": "Suggests" }, { "package": "rlang", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "rstanarm", "role": "Suggests" }, { "package": "scales", "version": ">= 1.4.0", "role": "Suggests" }, { "package": "splines", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.3.0", "role": "Suggests" }, { "package": "tidygraph", "role": "Suggests" }, { "package": "vdiffr", "version": ">= 1.0.8", "role": "Suggests" } ], "_owner": "easystats", "_selfowned": true, "_usedby": 5, "_updates": [ { "week": "2025-46", "n": 1 }, { "week": "2025-49", "n": 1 }, { "week": "2026-02", "n": 1 }, { "week": "2026-05", "n": 17 }, { "week": "2026-10", "n": 1 }, { "week": "2026-14", "n": 1 }, { "week": "2026-17", "n": 1 }, { "week": "2026-18", "n": 2 }, { "week": "2026-20", "n": 7 }, { "week": "2026-21", "n": 16 }, { "week": "2026-22", "n": 4 }, { "week": "2026-23", "n": 5 }, { "week": "2026-24", "n": 1 }, { "week": "2026-26", "n": 8 }, { "week": "2026-27", "n": 8 }, { "week": "2026-28", "n": 1 }, { "week": "2026-30", "n": 5 }, { "week": "2026-31", "n": 1 }, { "week": "2026-32", "n": 3 }, { "week": "2026-35", "n": 1 }, { "week": "2026-36", "n": 2 }, { "week": "2026-40", "n": 2 }, { "week": "2026-42", "n": 23 }, { "week": "2026-43", "n": 5 }, { "week": "2026-44", "n": 1 }, { "week": "2026-45", "n": 4 } ], "_tags": [ { "name": "v0.13.0", "date": "2026-01-30" }, { "name": "v0.14.0", "date": "2026-05-24" }, { "name": "v0.14.1", "date": "2026-06-29" }, { "name": "v0.14.2", "date": "2026-09-01" }, { "name": "v0.15.0", "date": "2026-10-16" } ], "_topics": [ "data-visualization", "easystats", "ggplot2", "hacktoberfest", "plotting", "see", "statistics", "visualisation", "visualization" ], "_stars": 956, "_contributors": [ { "user": "strengejacke", "count": 1083, "uuid": 26301769 }, { "user": "indrajeetpatil", "count": 402, "uuid": 11330453 }, { "user": "bwiernik", "count": 106, "uuid": 4773225 }, { "user": "dominiquemakowski", "count": 101, "uuid": 8875533 }, { "user": "mattansb", "count": 58, "uuid": 35330040 }, { "user": "jmgirard", "count": 21, "uuid": 6829033 }, { "user": "etiennebacher", "count": 15, "uuid": 52219252 }, { "user": "pdwaggoner", "count": 13, "uuid": 31326382 }, { "user": "rempsyc", "count": 12, "uuid": 13123390 }, { "user": "jeffreyrstevens", "count": 6, "uuid": 51374986 }, { "user": "jdtrat", "count": 3, "uuid": 51417262 }, { "user": "haomeng797-ship-it", "count": 3, "uuid": 251798069 }, { "user": "anamasgard", "count": 2, "uuid": 137998824 }, { "user": "copilot", "count": 2, "uuid": 198982749 }, { "user": "jbogomolovas2", "count": 2, "uuid": 105531636 }, { "user": "elinw", "count": 1, "uuid": 754813 }, { "user": "tolgakurtuluss", "count": 1, "uuid": 22731161 } ], "_userbio": { "uuid": 47102598, "type": "organization", "name": "easystats", "followers": 576, "description": "Make R stats easy!" }, "_downloads": { "count": 27721, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/see" }, "_mentions": 3, "_devurl": "https://github.com/easystats/see", "_pkgdown": "https://easystats.github.io/see/", "_searchresults": 2524, "_rbuild": "4.6.2", "_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/see.html", "LICENSE" ], "_homeurl": "https://github.com/easystats/see", "_realowner": "easystats", "_cranurl": true, "_releases": [ { "version": "0.1.0", "date": "2019-05-24" }, { "version": "0.2.0", "date": "2019-06-19" }, { "version": "0.2.1", "date": "2019-08-01" }, { "version": "0.3.0", "date": "2019-11-19" }, { "version": "0.4.0", "date": "2020-01-15" }, { "version": "0.4.1", "date": "2020-03-06" }, { "version": "0.5.0", "date": "2020-04-25" }, { "version": "0.5.1", "date": "2020-06-13" }, { "version": "0.5.2", "date": "2020-07-27" }, { "version": "0.6.0", "date": "2020-09-13" }, { "version": "0.6.1", "date": "2020-12-06" }, { "version": "0.6.2", "date": "2021-02-04" }, { "version": "0.6.3", "date": "2021-04-09" }, { "version": "0.6.4", "date": "2021-05-29" }, { "version": "0.6.7", "date": "2021-08-23" }, { "version": "0.6.8", "date": "2021-10-03" }, { "version": "0.6.9", "date": "2022-02-15" }, { "version": "0.7.0", "date": "2022-03-31" }, { "version": "0.7.1", "date": "2022-06-20" }, { "version": "0.7.2", "date": "2022-08-10" }, { "version": "0.7.3", "date": "2022-09-20" }, { "version": "0.7.4", "date": "2022-11-26" }, { "version": "0.7.5", "date": "2023-03-23" }, { "version": "0.8.0", "date": "2023-06-05" }, { "version": "0.8.1", "date": "2023-11-03" }, { "version": "0.8.2", "date": "2024-02-14" }, { "version": "0.8.3", "date": "2024-03-24" }, { "version": "0.8.4", "date": "2024-04-29" }, { "version": "0.8.5", "date": "2024-07-17" }, { "version": "0.9.0", "date": "2024-09-06" }, { "version": "0.10.0", "date": "2025-01-22" }, { "version": "0.11.0", "date": "2025-03-11" }, { "version": "0.12.0", "date": "2025-09-14" }, { "version": "0.13.0", "date": "2026-01-30" }, { "version": "0.14.0", "date": "2026-05-24" }, { "version": "0.14.1", "date": "2026-06-29" }, { "version": "0.14.2", "date": "2026-09-08" }, { "version": "0.15.0", "date": "2026-10-16" } ], "_exports": [ "add_plot_attributes", "bluebrown_colors", "coord_radar", "data_plot", "flat_colors", "geom_binomdensity", "geom_count_borderless", "geom_count_halo", "geom_count2", "geom_from_list", "geom_jitter_borderless", "geom_jitter_halo", "geom_jitter2", "geom_lightbeam", "geom_point_borderless", "geom_point_halo", "geom_point2", "geom_pointrange_borderless", "geom_pointrange_halo", "geom_pointrange2", "geom_pooljitter", "geom_poolpoint", "geom_raincloud", "geom_violindot", "geom_violinhalf", "GeomLightbeam", "geoms_from_list", "golden_ratio", "material_colors", "metro_colors", "oi_colors", "okabeito_colors", "palette_bluebrown", "palette_colorhex", "palette_flat", "palette_material", "palette_metro", "palette_oi", "palette_okabeito", "palette_pizza", "palette_see", "palette_social", "pizza_colors", "plots", "scale_color_bluebrown", "scale_color_bluebrown_c", "scale_color_bluebrown_d", "scale_color_colorhex", "scale_color_colorhex_c", "scale_color_colorhex_d", "scale_color_flat", "scale_color_flat_c", "scale_color_flat_d", "scale_color_material", "scale_color_material_c", "scale_color_material_d", "scale_color_metro", "scale_color_metro_c", "scale_color_metro_d", "scale_color_oi", "scale_color_okabeito", "scale_color_pizza", "scale_color_pizza_c", "scale_color_pizza_d", "scale_color_see", "scale_color_see_c", "scale_color_see_d", "scale_color_social", "scale_color_social_c", "scale_color_social_d", "scale_colour_bluebrown", "scale_colour_bluebrown_c", "scale_colour_bluebrown_d", "scale_colour_colorhex", "scale_colour_colorhex_c", "scale_colour_colorhex_d", "scale_colour_flat", "scale_colour_flat_c", "scale_colour_flat_d", "scale_colour_material", "scale_colour_material_c", "scale_colour_material_d", "scale_colour_metro", "scale_colour_metro_c", "scale_colour_metro_d", "scale_colour_oi", "scale_colour_okabeito", "scale_colour_pizza", "scale_colour_pizza_c", "scale_colour_pizza_d", "scale_colour_see", "scale_colour_see_c", "scale_colour_see_d", "scale_colour_social", "scale_colour_social_c", "scale_colour_social_d", "scale_fill_bluebrown", "scale_fill_bluebrown_c", "scale_fill_bluebrown_d", "scale_fill_colorhex", "scale_fill_colorhex_c", "scale_fill_colorhex_d", "scale_fill_flat", "scale_fill_flat_c", "scale_fill_flat_d", "scale_fill_material", "scale_fill_material_c", "scale_fill_material_d", "scale_fill_metro", "scale_fill_metro_c", "scale_fill_metro_d", "scale_fill_oi", "scale_fill_okabeito", "scale_fill_pizza", "scale_fill_pizza_c", "scale_fill_pizza_d", "scale_fill_see", "scale_fill_see_c", "scale_fill_see_d", "scale_fill_social", "scale_fill_social_c", "scale_fill_social_d", "see_colors", "social_colors", "theme_abyss", "theme_azurelight", "theme_blackboard", "theme_lucid", "theme_modern", "theme_radar", "theme_radar_dark" ], "_help": [ { "page": "add_plot_attributes", "title": "Complete figure with its attributes", "topics": [ "add_plot_attributes" ] }, { "page": "bluebrown_colors", "title": "Extract blue-brown colors as hex codes", "topics": [ "bluebrown_colors" ] }, { "page": "coord_radar", "title": "Radar coordinate system", "topics": [ "coord_radar" ] }, { "page": "data_plot", "title": "Prepare objects for plotting or plot objects", "topics": [ "data_plot", "data_plot.compare_performance" ] }, { "page": "flat_colors", "title": "Extract Flat UI colors as hex codes", "topics": [ "flat_colors" ] }, { "page": "geom_binomdensity", "title": "Add dot-densities for binary 'y' variables", "topics": [ "geom_binomdensity" ] }, { "page": "geom_from_list", "title": "Create ggplot2 geom(s) from a list", "topics": [ "geoms_from_list", "geom_from_list" ] }, { "page": "geom_lightbeam", "title": "Lighthouse beams", "topics": [ "GeomLightbeam", "geom_lightbeam" ] }, { "page": "geom_point2", "title": "Better looking points", "topics": [ "geom_count2", "geom_count_borderless", "geom_count_halo", "geom_jitter2", "geom_jitter_borderless", "geom_jitter_halo", "geom_point2", "geom_pointrange2", "geom_pointrange_borderless", "geom_pointrange_halo", "geom_point_borderless", "geom_point_halo" ] }, { "page": "geom_poolpoint", "title": "Pool ball points", "topics": [ "geom_pooljitter", "geom_poolpoint" ] }, { "page": "geom_raincloud", "title": "Raincloud plot", "topics": [ "geom_raincloud" ] }, { "page": "geom_violindot", "title": "Half-violin Half-dot plot", "topics": [ "geom_violindot" ] }, { "page": "geom_violinhalf", "title": "Half-violin plot", "topics": [ "geom_violinhalf" ] }, { "page": "golden_ratio", "title": "Golden Ratio", "topics": [ "golden_ratio" ] }, { "page": "material_colors", "title": "Extract material design colors as hex codes", "topics": [ "material_colors" ] }, { "page": "metro_colors", "title": "Extract Metro colors as hex codes", "topics": [ "metro_colors" ] }, { "page": "okabeito_colors", "title": "Extract Okabe-Ito colors as hex codes", "topics": [ "oi_colors", "okabeito_colors" ] }, { "page": "palette_bluebrown", "title": "Blue-brown design color palette", "topics": [ "palette_bluebrown" ] }, { "page": "palette_colorhex", "title": "Color palettes from color-hex.com.", "topics": [ "palette_colorhex" ] }, { "page": "palette_flat", "title": "Flat UI color palette", "topics": [ "palette_flat" ] }, { "page": "palette_material", "title": "Material design color palette", "topics": [ "palette_material" ] }, { "page": "palette_metro", "title": "Metro color palette", "topics": [ "palette_metro" ] }, { "page": "palette_okabeito", "title": "Okabe-Ito color palette", "topics": [ "palette_oi", "palette_okabeito" ] }, { "page": "palette_pizza", "title": "Pizza color palette", "topics": [ "palette_pizza" ] }, { "page": "palette_see", "title": "See design color palette", "topics": [ "palette_see" ] }, { "page": "palette_social", "title": "Social color palette", "topics": [ "palette_social" ] }, { "page": "pizza_colors", "title": "Extract pizza colors as hex codes", "topics": [ "pizza_colors" ] }, { "page": "plot.datawizard_table", "title": "Plot tabulated data.", "topics": [ "plot.datawizard_table", "plot.datawizard_tables" ] }, { "page": "plot.see_bayesfactor_models", "title": "Plot method for Bayes Factors for model comparison", "topics": [ "plot.see_bayesfactor_models" ] }, { "page": "plot.see_bayesfactor_parameters", "title": "Plot method for Bayes Factors for a single parameter", "topics": [ "plot.see_bayesfactor_parameters" ] }, { "page": "plot.see_check_collinearity", "title": "Plot method for multicollinearity checks", "topics": [ "plot.see_check_collinearity" ] }, { "page": "plot.see_check_dag", "title": "Plot method for check DAGs", "topics": [ "plot.see_check_dag" ] }, { "page": "plot.see_check_distribution", "title": "Plot method for classifying the distribution of a model-family", "topics": [ "plot.see_check_distribution" ] }, { "page": "plot.see_check_heteroscedasticity", "title": "Plot method for (non-)constant error variance checks", "topics": [ "plot.see_check_heteroscedasticity" ] }, { "page": "plot.see_check_homogeneity", "title": "Plot method for homogeneity of variances checks", "topics": [ "plot.see_check_homogeneity" ] }, { "page": "plot.see_check_model", "title": "Plot method for checking model assumptions", "topics": [ "plot.see_check_model" ] }, { "page": "plot.see_check_normality", "title": "Plot method for check model for (non-)normality of residuals", "topics": [ "plot.see_check_normality" ] }, { "page": "plot.see_check_outliers", "title": "Plot method for checking outliers", "topics": [ "plot.see_check_outliers" ] }, { "page": "plot.see_check_priors", "title": "Plot method for prior predictive checks", "topics": [ "plot.see_check_priors" ] }, { "page": "plot.see_compare_parameters", "title": "Plot method for comparison of model parameters", "topics": [ "plot.see_compare_parameters" ] }, { "page": "plot.see_compare_performance", "title": "Plot method for comparing model performances", "topics": [ "plot.see_compare_performance" ] }, { "page": "plot.see_dw_groupmeans", "title": "Plot method for grouped means.", "topics": [ "plot.see_dw_groupmeans" ] }, { "page": "plot.see_effectsize_table", "title": "Plot method for effect size tables", "topics": [ "plot.see_effectsize_table" ] }, { "page": "plot.see_equivalence_test", "title": "Plot method for (conditional) equivalence testing", "topics": [ "plot.see_equivalence_test", "plot.see_equivalence_test_effectsize", "plot.see_equivalence_test_lm" ] }, { "page": "plot.see_estimate_contrasts", "title": "Plot method for estimating contrasts", "topics": [ "plot.see_estimate_contrasts" ] }, { "page": "plot.see_estimate_density", "title": "Plot method for density estimation of posterior samples", "topics": [ "plot.see_estimate_density" ] }, { "page": "plot.see_hdi", "title": "Plot method for uncertainty or credible intervals", "topics": [ "plot.see_hdi" ] }, { "page": "plot.see_n_factors", "title": "Plot method for numbers of clusters to extract or factors to retain", "topics": [ "plot.see_n_factors" ] }, { "page": "plot.see_p_direction", "title": "Plot method for probability of direction", "topics": [ "plot.see_p_direction" ] }, { "page": "plot.see_p_function", "title": "Plot method for plotting p-functions (aka consonance functions)", "topics": [ "plot.see_p_function" ] }, { "page": "plot.see_p_significance", "title": "Plot method for practical significance", "topics": [ "plot.see_p_significance" ] }, { "page": "plot.see_parameters_brms_meta", "title": "Plot method for Model Parameters from Bayesian Meta-Analysis", "topics": [ "plot.see_parameters_brms_meta" ] }, { "page": "plot.see_parameters_distribution", "title": "Plot method for describing distributions of vectors", "topics": [ "plot.see_parameters_distribution" ] }, { "page": "plot.see_parameters_model", "title": "Plot method for model parameters", "topics": [ "plot.see_parameters_model", "plot.see_parameters_sem" ] }, { "page": "plot.see_parameters_pca", "title": "Plot method for principal component analysis", "topics": [ "plot.see_parameters_pca" ] }, { "page": "plot.see_parameters_simulate", "title": "Plot method for simulated model parameters", "topics": [ "plot.see_parameters_simulate" ] }, { "page": "plot.see_performance_roc", "title": "Plot method for ROC curves", "topics": [ "plot.see_performance_roc" ] }, { "page": "plot.see_performance_simres", "title": "Plot method for check model for (non-)normality of residuals", "topics": [ "plot.see_performance_simres" ] }, { "page": "plot.see_point_estimate", "title": "Plot method for point estimates of posterior samples", "topics": [ "plot.see_point_estimate" ] }, { "page": "plot.see_rope", "title": "Plot method for Region of Practical Equivalence", "topics": [ "plot.see_rope" ] }, { "page": "plot.see_si", "title": "Plot method for support intervals", "topics": [ "plot.see_si" ] }, { "page": "plots", "title": "Multiple plots side by side", "topics": [ "plots" ] }, { "page": "print.see_performance_pp_check", "title": "Plot method for posterior predictive checks", "topics": [ "plot.see_performance_pp_check", "print.see_performance_pp_check" ] }, { "page": "scale_color_bluebrown", "title": "Blue-brown color palette", "topics": [ "scale_color_bluebrown", "scale_color_bluebrown_c", "scale_color_bluebrown_d", "scale_colour_bluebrown", "scale_colour_bluebrown_c", "scale_colour_bluebrown_d", "scale_fill_bluebrown", "scale_fill_bluebrown_c", "scale_fill_bluebrown_d" ] }, { "page": "scale_color_colorhex", "title": "Color palettes from color-hex", "topics": [ "scale_color_colorhex", "scale_color_colorhex_c", "scale_color_colorhex_d", "scale_colour_colorhex", "scale_colour_colorhex_c", "scale_colour_colorhex_d", "scale_fill_colorhex", "scale_fill_colorhex_c", "scale_fill_colorhex_d" ] }, { "page": "scale_color_flat", "title": "Flat UI color palette", "topics": [ "scale_color_flat", "scale_color_flat_c", "scale_color_flat_d", "scale_colour_flat", "scale_colour_flat_c", "scale_colour_flat_d", "scale_fill_flat", "scale_fill_flat_c", "scale_fill_flat_d" ] }, { "page": "scale_color_material", "title": "Material design color palette", "topics": [ "scale_color_material", "scale_color_material_c", "scale_color_material_d", "scale_colour_material", "scale_colour_material_c", "scale_colour_material_d", "scale_fill_material", "scale_fill_material_c", "scale_fill_material_d" ] }, { "page": "scale_color_metro", "title": "Metro color palette", "topics": [ "scale_color_metro", "scale_color_metro_c", "scale_color_metro_d", "scale_colour_metro", "scale_colour_metro_c", "scale_colour_metro_d", "scale_fill_metro", "scale_fill_metro_c", "scale_fill_metro_d" ] }, { "page": "scale_color_okabeito", "title": "Okabe-Ito color palette", "topics": [ "scale_color_oi", "scale_color_okabeito", "scale_colour_oi", "scale_colour_okabeito", "scale_fill_oi", "scale_fill_okabeito" ] }, { "page": "scale_color_pizza", "title": "Pizza color palette", "topics": [ "scale_color_pizza", "scale_color_pizza_c", "scale_color_pizza_d", "scale_colour_pizza", "scale_colour_pizza_c", "scale_colour_pizza_d", "scale_fill_pizza", "scale_fill_pizza_c", "scale_fill_pizza_d" ] }, { "page": "scale_color_see", "title": "See color palette", "topics": [ "scale_color_see", "scale_color_see_c", "scale_color_see_d", "scale_colour_see", "scale_colour_see_c", "scale_colour_see_d", "scale_fill_see", "scale_fill_see_c", "scale_fill_see_d" ] }, { "page": "scale_color_social", "title": "Social color palette", "topics": [ "scale_color_social", "scale_color_social_c", "scale_color_social_d", "scale_colour_social", "scale_colour_social_c", "scale_colour_social_d", "scale_fill_social", "scale_fill_social_c", "scale_fill_social_d" ] }, { "page": "see_colors", "title": "Extract See colors as hex codes", "topics": [ "see_colors" ] }, { "page": "social_colors", "title": "Extract Social colors as hex codes", "topics": [ "social_colors" ] }, { "page": "theme_abyss", "title": "Abyss theme", "topics": [ "theme_abyss" ] }, { "page": "theme_azurelight", "title": "Azurelight theme", "topics": [ "theme_azurelight" ] }, { "page": "theme_blackboard", "title": "Blackboard dark theme", "topics": [ "theme_blackboard" ] }, { "page": "theme_lucid", "title": "Lucid theme", "topics": [ "theme_lucid" ] }, { "page": "theme_modern", "title": "The easystats' minimal theme", "topics": [ "theme_modern" ] }, { "page": "theme_radar", "title": "Themes for radar plots", "topics": [ "theme_radar", "theme_radar_dark" ] } ], "_pkglogo": "https://github.com/easystats/see/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/easystats/see/raw/HEAD/README.md", "_rundeps": [ "bayestestR", "cli", "correlation", "cpp11", "datawizard", "effectsize", "farver", "ggplot2", "glue", "gtable", "insight", "isoband", "labeling", "lifecycle", "modelbased", "parameters", "patchwork", "performance", "R6", "RColorBrewer", "rlang", "S7", "scales", "vctrs", "viridisLite", "withr" ], "_score": 13.796631984432581, "_indexed": true, "_nocasepkg": "see", "_universes": [ "easystats" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.15.0.7", "date": "2026-11-06T21:47:57.000Z", "distro": "resolute", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/db9b73f7158ce36a7ead1aeb4b03d39cd57721924bc0b731ba4ae1e6321e3c7c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" }, { "r": "4.6.2", "os": "linux", "version": "0.15.0.7", "date": "2026-11-06T21:50:51.000Z", "distro": "resolute", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/24b84a89c9469501035d942c06720d0ce8524ecf933cbcf7995368160d31c82e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" }, { "r": "4.5.3", "os": "mac", "version": "0.15.0.7", "date": "2026-11-06T22:01:39.000Z", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/262f2c1ec231c9614817bf0c441e864bad92aa544c8cea2991d820f50c47b8bf", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" }, { "r": "4.6.2", "os": "mac", "version": "0.15.0.7", "date": "2026-11-06T22:01:39.000Z", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/6cf85024c60085d478691e0ae3868a6907263facc285b07df0413bd76cef1701", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" }, { "r": "4.6.0", "os": "wasm", "version": "0.15.0.7", "date": "2026-11-06T21:47:13.000Z", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/3d18ecb144099adde06173af814fc61de221677a683675bbc1d7b5869cb31528", "status": "success", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" }, { "r": "4.7.0", "os": "win", "version": "0.15.0.7", "date": "2026-11-06T21:46:11.000Z", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/2b3a43682280d132ce69d5196e788fb312dae3d26315635ef3194a6edc01ec57", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" }, { "r": "4.5.3", "os": "win", "version": "0.15.0.7", "date": "2026-11-06T21:46:23.000Z", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/ac8a262480755977744062d4dd2ab73ad73bd36954283e05b5e7aac731cc310e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" }, { "r": "4.6.2", "os": "win", "version": "0.15.0.7", "date": "2026-11-06T21:46:24.000Z", "commit": "ae212b017a52d05805848e77b9a2a26408417243", "fileid": "https://r2.ropensci.org/c969f96bb945d1a8f51966f55802d5fc540d652cc0ce1914bbcf5adde1a69b4b", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/easystats/actions/runs/42298369518" } ] }