{
"_id": "6a1efceeb401979e734198e4",
"Package": "ggdag",
"Title": "Analyze and Create Elegant Directed Acyclic Graphs",
"Version": "0.2.13.9000",
"Authors@R": "person(\"Malcolm\", \"Barrett\", , \"malcolmbarrett@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-0299-5825\"))",
"Description": "Tidy, analyze, and plot directed acyclic graphs (DAGs).\n'ggdag' is built on top of 'dagitty', an R package that uses\nthe 'DAGitty' web tool () for creating\nand analyzing DAGs. 'ggdag' makes it easy to tidy and plot\n'dagitty' objects using 'ggplot2' and 'ggraph', as well as\ncommon analytic and graphical functions, such as determining\nadjustment sets and node relationships.",
"License": "MIT + file LICENSE",
"URL": "https://github.com/r-causal/ggdag,\nhttps://r-causal.github.io/ggdag/",
"BugReports": "https://github.com/r-causal/ggdag/issues",
"VignetteBuilder": "knitr",
"Config/testthat/edition": "3",
"Encoding": "UTF-8",
"Language": "en-US",
"Roxygen": "list(markdown = TRUE)",
"RoxygenNote": "7.3.3",
"Config/testthat/parallel": "true",
"Remotes": [
"teunbrand/ggarrow"
],
"Config/pak/sysreqs": "libfontconfig1-dev libfreetype6-dev libglpk-dev\nlibicu-dev libxml2-dev libssl-dev libnode-dev",
"Repository": "https://r-causal.r-universe.dev",
"Date/Publication": "2026-03-17 20:33:14 UTC",
"RemoteUrl": "https://github.com/r-causal/ggdag",
"RemoteRef": "HEAD",
"RemoteSha": "71997d874337e74eef3f55918b9ac535426f7c4a",
"NeedsCompilation": "no",
"Packaged": {
"Date": "2026-05-18 10:02:03 UTC",
"User": "root"
},
"Author": "Malcolm Barrett [aut, cre] (ORCID:\n)",
"Maintainer": "Malcolm Barrett ",
"MD5sum": "eb72bbf4d23142f8355948c40d1912b6",
"_user": "r-causal",
"_type": "src",
"_file": "ggdag_0.2.13.9000.tar.gz",
"_fileid": "8132a24d840f2cfadd71f434267f6a2592715c5df72936c2860da580c904a496",
"_filesize": 4275477,
"_sha256": "8132a24d840f2cfadd71f434267f6a2592715c5df72936c2860da580c904a496",
"_created": "2026-05-18T10:02:03.000Z",
"_published": "2026-06-02T15:55:26.700Z",
"_distro": "noble",
"_jobs": [
{
"job": 79113809003,
"time": 326,
"config": "linux-devel-x86_64",
"r": "4.7.0",
"check": "OK",
"artifact": "7054956820"
},
{
"job": 79113808865,
"time": 298,
"config": "linux-release-x86_64",
"r": "4.6.0",
"check": "OK",
"artifact": "7054947428"
},
{
"job": 79113809339,
"time": 262,
"config": "macos-oldrel-arm64",
"r": "4.5.3",
"check": "OK",
"artifact": "7054935671"
},
{
"job": 79113809081,
"time": 272,
"config": "macos-release-arm64",
"r": "4.6.0",
"check": "OK",
"artifact": "7054938376"
},
{
"job": 79113810247,
"time": 240,
"config": "source",
"r": "4.6.0",
"check": "OK",
"artifact": "7054847215"
},
{
"job": 79113808233,
"time": 126,
"config": "wasm-release",
"r": "4.6.0",
"check": "OK",
"artifact": "7362951664"
},
{
"job": 79113809099,
"time": 328,
"config": "windows-devel",
"r": "4.7.0",
"check": "OK",
"artifact": "7054958314"
},
{
"job": 79113809940,
"time": 367,
"config": "windows-oldrel",
"r": "4.5.3",
"check": "OK",
"artifact": "7054970171"
},
{
"job": 79113808933,
"time": 402,
"config": "windows-release",
"r": "4.6.0",
"check": "OK",
"artifact": "7054981701"
}
],
"_buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576",
"_status": "success",
"_host": "GitHub-Actions",
"_upstream": "https://github.com/r-causal/ggdag",
"_commit": {
"id": "71997d874337e74eef3f55918b9ac535426f7c4a",
"author": "Malcolm Barrett ",
"committer": "GitHub ",
"message": "Merge pull request #235 from r-causal/curves_and_glyphs\n\nfix ggarrow engine for more complex quick plotters",
"time": 1773779594
},
"_maintainer": {
"name": "Malcolm Barrett",
"email": "malcolmbarrett@gmail.com",
"login": "malcolmbarrett",
"mastodon": "@malcolmbarrett@mstdn.jp",
"bluesky": "@malcolmbarrett.malco.io",
"orcid": "0000-0003-0299-5825",
"description": "Open-source data science. Ph.D. in Epidemiology",
"uuid": 23123711
},
"_registered": true,
"_dependencies": [
{
"package": "R",
"version": ">= 4.1.0",
"role": "Depends"
},
{
"package": "cli",
"version": ">= 3.0.0",
"role": "Imports"
},
{
"package": "dagitty",
"role": "Imports"
},
{
"package": "dplyr",
"role": "Imports"
},
{
"package": "forcats",
"role": "Imports"
},
{
"package": "ggarrow",
"version": ">= 0.1.1.9000",
"role": "Imports"
},
{
"package": "ggplot2",
"version": ">= 3.0.0",
"role": "Imports"
},
{
"package": "ggraph",
"version": ">= 2.0.0",
"role": "Imports"
},
{
"package": "ggrepel",
"version": ">= 0.9.7",
"role": "Imports"
},
{
"package": "igraph",
"role": "Imports"
},
{
"package": "lifecycle",
"version": ">= 0.2.0",
"role": "Imports"
},
{
"package": "magrittr",
"role": "Imports"
},
{
"package": "pillar",
"role": "Imports"
},
{
"package": "purrr",
"role": "Imports"
},
{
"package": "rlang",
"role": "Imports"
},
{
"package": "stringr",
"role": "Imports"
},
{
"package": "tibble",
"role": "Imports"
},
{
"package": "tidygraph",
"role": "Imports"
},
{
"package": "covr",
"role": "Suggests"
},
{
"package": "knitr",
"role": "Suggests"
},
{
"package": "rmarkdown",
"role": "Suggests"
},
{
"package": "spelling",
"role": "Suggests"
},
{
"package": "testthat",
"version": ">= 3.0.0",
"role": "Suggests"
},
{
"package": "vdiffr",
"version": ">= 1.0.2",
"role": "Suggests"
},
{
"package": "withr",
"role": "Suggests"
}
],
"_owner": "r-causal",
"_selfowned": true,
"_usedby": 10,
"_updates": [
{
"week": "2025-32",
"n": 8
},
{
"week": "2025-33",
"n": 8
},
{
"week": "2025-34",
"n": 11
},
{
"week": "2026-08",
"n": 1
},
{
"week": "2026-11",
"n": 11
},
{
"week": "2026-12",
"n": 3
}
],
"_tags": [],
"_topics": [
"causal-inference",
"dag",
"ggplot-extension"
],
"_stars": 464,
"_contributors": [
{
"user": "malcolmbarrett",
"count": 648,
"uuid": 23123711
},
{
"user": "copilot",
"count": 12,
"uuid": 198982749
},
{
"user": "pgcudahy",
"count": 5,
"uuid": 5791816
},
{
"user": "teunbrand",
"count": 3,
"uuid": 49372158
},
{
"user": "henningte",
"count": 3,
"uuid": 34153309
}
],
"_userbio": {
"uuid": 129535100,
"type": "organization",
"name": "Causal Inference in R",
"description": "Tools and educational material for causal inference in R"
},
"_downloads": {
"count": 9666,
"source": "https://cranlogs.r-pkg.org/downloads/total/last-month/ggdag"
},
"_devurl": "https://github.com/r-causal/ggdag",
"_pkgdown": "https://r-causal.github.io/ggdag/",
"_searchresults": 2664,
"_rbuild": "4.6.0",
"_assets": [
"extra/citation.cff",
"extra/citation.html",
"extra/citation.json",
"extra/citation.txt",
"extra/contents.json",
"extra/ggdag.html",
"extra/NEWS.html",
"extra/NEWS.txt",
"extra/readme.html",
"extra/readme.md",
"manual.pdf"
],
"_homeurl": "https://github.com/r-causal/ggdag",
"_realowner": "r-causal",
"_cranurl": true,
"_releases": [
{
"version": "0.1.0",
"date": "2018-03-28"
},
{
"version": "0.2.0",
"date": "2019-09-12"
},
{
"version": "0.2.1",
"date": "2019-12-06"
},
{
"version": "0.2.2",
"date": "2020-02-13"
},
{
"version": "0.2.3",
"date": "2021-01-12"
},
{
"version": "0.2.4",
"date": "2021-10-10"
},
{
"version": "0.2.5",
"date": "2022-07-16"
},
{
"version": "0.2.6",
"date": "2022-08-26"
},
{
"version": "0.2.7",
"date": "2022-10-29"
},
{
"version": "0.2.8",
"date": "2023-03-17"
},
{
"version": "0.2.9",
"date": "2023-05-22"
},
{
"version": "0.2.10",
"date": "2023-05-29"
},
{
"version": "0.2.11",
"date": "2024-01-24"
},
{
"version": "0.2.12",
"date": "2024-03-08"
},
{
"version": "0.2.13",
"date": "2024-07-22"
}
],
"_exports": [
"%>%",
"activate_collider_paths",
"adjust_for",
"aes_dag",
"arrange_.tidy_dagitty",
"as_tidy_dagitty",
"as.tbl.tidy_dagitty",
"butterfly_bias",
"collider_triangle",
"confounder_triangle",
"control_for",
"coords2df",
"coords2list",
"curve_edge",
"curved",
"dag",
"dag_adjustment_sets",
"dag_label",
"dag_paths",
"dag_prune",
"dag_saturate",
"dagify",
"draw_key_dag_collider",
"draw_key_dag_combined",
"draw_key_dag_edge",
"draw_key_dag_point",
"edge_backdoor",
"expand_plot",
"filter",
"filter_.tidy_dagitty",
"geom_dag",
"geom_dag_arrow",
"geom_dag_arrow_arc",
"geom_dag_arrows",
"geom_dag_collider_edges",
"geom_dag_edges",
"geom_dag_edges_arc",
"geom_dag_edges_diagonal",
"geom_dag_edges_fan",
"geom_dag_edges_link",
"geom_dag_label",
"geom_dag_label_repel",
"geom_dag_label_repel2",
"geom_dag_node",
"geom_dag_point",
"geom_dag_text",
"geom_dag_text_repel",
"geom_dag_text_repel2",
"ggdag",
"ggdag_adjacent",
"ggdag_adjust",
"ggdag_adjustment_set",
"ggdag_ancestors",
"ggdag_butterfly_bias",
"ggdag_canonical",
"ggdag_children",
"ggdag_classic",
"ggdag_collider",
"ggdag_collider_triangle",
"ggdag_conditional_independence",
"ggdag_confounder_triangle",
"ggdag_dconnected",
"ggdag_defaults",
"ggdag_descendants",
"ggdag_drelationship",
"ggdag_dseparated",
"ggdag_equivalent_class",
"ggdag_equivalent_dags",
"ggdag_exogenous",
"ggdag_instrumental",
"ggdag_m_bias",
"ggdag_markov_blanket",
"ggdag_mediation_triangle",
"ggdag_option",
"ggdag_option_proportional",
"ggdag_options_get",
"ggdag_options_reset",
"ggdag_options_set",
"ggdag_parents",
"ggdag_paths",
"ggdag_paths_fan",
"ggdag_quartet_collider",
"ggdag_quartet_confounder",
"ggdag_quartet_m_bias",
"ggdag_quartet_mediator",
"ggdag_quartet_time_collider",
"ggdag_status",
"has_labels",
"is_acyclic",
"is_adjacent",
"is_adjustment_set",
"is_ancestor",
"is_child",
"is_collider",
"is_confounder",
"is_d_connected",
"is_d_separated",
"is_descendant",
"is_downstream_collider",
"is_exogenous",
"is_exposure",
"is_instrumental",
"is_latent",
"is_outcome",
"is_parent",
"is.tidy_dagitty",
"label",
"label<-",
"m_bias",
"mediation_triangle",
"mutate_.tidy_dagitty",
"node_adjacent",
"node_ancestors",
"node_canonical",
"node_children",
"node_collider",
"node_dconnected",
"node_descendants",
"node_drelationship",
"node_dseparated",
"node_equivalent_class",
"node_equivalent_dags",
"node_exogenous",
"node_instrumental",
"node_markov_blanket",
"node_parents",
"node_status",
"pull_dag",
"pull_dag_data",
"quartet_collider",
"quartet_confounder",
"quartet_m_bias",
"quartet_mediator",
"quartet_time_collider",
"query_adjustment_sets",
"query_ancestors",
"query_children",
"query_colliders",
"query_conditional_independence",
"query_dconnected",
"query_descendants",
"query_dseparated",
"query_exogenous",
"query_instrumental",
"query_markov_blanket",
"query_parents",
"query_paths",
"query_status",
"remove_axes",
"remove_grid",
"scale_adjusted",
"scale_dag",
"select_.tidy_dagitty",
"set_curve_edges",
"simulate_data",
"slice_.tidy_dagitty",
"summarise_.tidy_dagitty",
"tbl_df.tidy_dagitty",
"test_conditional_independence",
"theme_dag",
"theme_dag_blank",
"theme_dag_gray",
"theme_dag_gray_grid",
"theme_dag_grey",
"theme_dag_grey_grid",
"theme_dag_grid",
"tidy_dagitty",
"time_ordered_coords",
"update_dag",
"update_dag_data<-",
"update_dag<-"
],
"_help": [
{
"page": "activate_collider_paths",
"title": "Activate paths opened by stratifying on a collider",
"topics": [
"activate_collider_paths"
]
},
{
"page": "control_for",
"title": "Adjust for variables and activate any biasing paths that result",
"topics": [
"Adjust for variables",
"adjust_for",
"control_for",
"ggdag_adjust"
]
},
{
"page": "aes_dag",
"title": "Define Aesthetics for Directed Acyclic Graphs (DAGs)",
"topics": [
"aes_dag"
]
},
{
"page": "as_tbl_graph",
"title": "Convert DAGS to tidygraph",
"topics": [
"as_tbl_graph",
"as_tbl_graph.dagitty",
"as_tbl_graph.tidy_dagitty"
]
},
{
"page": "as_tidy_dagitty",
"title": "Convert objects into 'tidy_dagitty' objects",
"topics": [
"as_tidy_dagitty",
"as_tidy_dagitty.dagitty",
"as_tidy_dagitty.data.frame",
"as_tidy_dagitty.list"
]
},
{
"page": "as.data.frame.tidy_dagitty",
"title": "Convert a 'tidy_dagitty' object to data.frame",
"topics": [
"as.data.frame.tidy_dagitty"
]
},
{
"page": "as.tbl.tidy_dagitty",
"title": "Convert a 'tidy_dagitty' object to tbl",
"topics": [
"as.tbl.tidy_dagitty",
"as_tibble.tidy_dagitty"
]
},
{
"page": "d_relationship",
"title": "D-relationship between variables",
"topics": [
"Assess d-separation between variables",
"ggdag_dconnected",
"ggdag_drelationship",
"ggdag_dseparated",
"node_dconnected",
"node_drelationship",
"node_dseparated"
]
},
{
"page": "variable_family",
"title": "Familial relationships between variables",
"topics": [
"Assess familial relationships between variables",
"ggdag_adjacent",
"ggdag_ancestors",
"ggdag_children",
"ggdag_descendants",
"ggdag_markov_blanket",
"ggdag_parents",
"node_adjacent",
"node_ancestors",
"node_children",
"node_descendants",
"node_markov_blanket",
"node_parents"
]
},
{
"page": "canonicalize",
"title": "Canonicalize a DAG",
"topics": [
"Canonicalize DAGs",
"ggdag_canonical",
"node_canonical"
]
},
{
"page": "colliders",
"title": "Find colliders",
"topics": [
"Colliders",
"ggdag_collider",
"node_collider"
]
},
{
"page": "coordinates",
"title": "Manipulate DAG coordinates",
"topics": [
"coordinates",
"coords2df",
"coords2list"
]
},
{
"page": "adjustment_sets",
"title": "Covariate Adjustment Sets",
"topics": [
"Covariate Adjustment Sets",
"dag_adjustment_sets",
"ggdag_adjustment_set"
]
},
{
"page": "curve_edge",
"title": "Add or update curvature for a single edge",
"topics": [
"curve_edge"
]
},
{
"page": "curved",
"title": "Mark an edge as curved in dagify formulas",
"topics": [
"curved"
]
},
{
"page": "dag",
"title": "Create a dagitty DAG",
"topics": [
"dag"
]
},
{
"page": "geom_dag_edge_functions",
"title": "Directed DAG edges",
"topics": [
"DAG Edges",
"geom_dag_edges_arc",
"geom_dag_edges_diagonal",
"geom_dag_edges_fan",
"geom_dag_edges_link"
]
},
{
"page": "label",
"title": "DAG labels",
"topics": [
"DAG Labels",
"dag_label",
"has_labels",
"label",
"label<-",
"label<-.dagitty",
"label<-.tidy_dagitty"
]
},
{
"page": "dag_saturate",
"title": "Saturate or prune an existing DAG",
"topics": [
"dag_prune",
"dag_saturate"
]
},
{
"page": "dagify",
"title": "Create a dagitty DAG using R-like syntax",
"topics": [
"dagify"
]
},
{
"page": "dplyr",
"title": "Dplyr verb methods for 'tidy_dagitty' objects",
"topics": [
"anti_join.tidy_dagitty",
"arrange.tidy_dagitty",
"arrange_.tidy_dagitty",
"distinct.tidy_dagitty",
"dplyr",
"filter.tidy_dagitty",
"filter_.tidy_dagitty",
"full_join.tidy_dagitty",
"group_by.tidy_dagitty",
"inner_join.tidy_dagitty",
"left_join.tidy_dagitty",
"mutate.tidy_dagitty",
"mutate_.tidy_dagitty",
"right_join.tidy_dagitty",
"select.tidy_dagitty",
"select_.tidy_dagitty",
"semi_join.tidy_dagitty",
"slice.tidy_dagitty",
"slice_.tidy_dagitty",
"summarise.tidy_dagitty",
"summarise_.tidy_dagitty",
"transmute.tidy_dagitty",
"ungroup.tidy_dagitty"
]
},
{
"page": "draw_key_dag_collider",
"title": "Collider pattern legend key (many-to-one)",
"topics": [
"draw_key_dag_collider"
]
},
{
"page": "draw_key_dag_combined",
"title": "Combined DAG legend key (horizontal node-edge-node)",
"topics": [
"draw_key_dag_combined"
]
},
{
"page": "draw_key_dag_edge",
"title": "DAG edge legend key (arrow only)",
"topics": [
"draw_key_dag_edge"
]
},
{
"page": "draw_key_dag_point",
"title": "DAG point legend key (25% size)",
"topics": [
"draw_key_dag_point"
]
},
{
"page": "edge_backdoor",
"title": "Classify DAG edges as backdoor or direct",
"topics": [
"edge_backdoor"
]
},
{
"page": "equivalent",
"title": "Generating Equivalent Models",
"topics": [
"Equivalent DAGs and Classes",
"ggdag_equivalent_class",
"ggdag_equivalent_dags",
"node_equivalent_class",
"node_equivalent_dags"
]
},
{
"page": "exogenous",
"title": "Find Exogenous Variables",
"topics": [
"Exogenous Variables",
"ggdag_exogenous",
"node_exogenous"
]
},
{
"page": "expand_plot",
"title": "Quickly scale the size of a ggplot",
"topics": [
"expand_plot"
]
},
{
"page": "fortify",
"title": "Fortify a 'tidy_dagitty' object for 'ggplot2'",
"topics": [
"fortify",
"fortify.dagitty",
"fortify.tidy_dagitty"
]
},
{
"page": "geom_dag",
"title": "Add common DAG layers to a ggplot",
"topics": [
"geom_dag"
]
},
{
"page": "geom_dag_arrow",
"title": "Directed DAG edges using ggarrow",
"topics": [
"geom_dag_arrow",
"geom_dag_arrows",
"geom_dag_arrow_arc"
]
},
{
"page": "geom_dag_collider_edges",
"title": "Edges for paths activated by stratification on colliders",
"topics": [
"geom_dag_collider_edges"
]
},
{
"page": "geom_dag_edges",
"title": "Directed and bidirected DAG edges",
"topics": [
"geom_dag_edges"
]
},
{
"page": "geom_dag_label",
"title": "Node text labels",
"topics": [
"geom_dag_label"
]
},
{
"page": "geom_dag_text",
"title": "Node text",
"topics": [
"geom_dag_text"
]
},
{
"page": "ggdag",
"title": "Quickly plot a DAG in ggplot2",
"topics": [
"ggdag"
]
},
{
"page": "ggdag_classic",
"title": "Quickly plot a DAG in ggplot2",
"topics": [
"ggdag_classic"
]
},
{
"page": "ggdag_options",
"title": "Global DAG Options",
"topics": [
"ggdag_defaults",
"ggdag_option",
"ggdag_options_get",
"ggdag_options_reset",
"ggdag_options_set",
"ggdag_option_proportional"
]
},
{
"page": "ggplot.tidy_dagitty",
"title": "Create a new ggplot",
"topics": [
"ggplot.dagitty",
"ggplot.tidy_dagitty"
]
},
{
"page": "repel",
"title": "Repulsive textual annotations",
"topics": [
"geom_dag_label_repel",
"geom_dag_label_repel2",
"geom_dag_text_repel",
"geom_dag_text_repel2",
"ggrepel functions"
]
},
{
"page": "instrumental",
"title": "Find Instrumental Variables",
"topics": [
"ggdag_instrumental",
"Instrumental Variables",
"node_instrumental"
]
},
{
"page": "is_confounder",
"title": "Assess if a variable confounds a relationship",
"topics": [
"is_confounder"
]
},
{
"page": "is_dag_properties",
"title": "Test DAG properties",
"topics": [
"is_acyclic",
"is_adjustment_set",
"is_dag_properties",
"is_d_connected",
"is_d_separated"
]
},
{
"page": "is_node_properties",
"title": "Test node properties",
"topics": [
"is_exogenous",
"is_exposure",
"is_instrumental",
"is_latent",
"is_node_properties",
"is_outcome"
]
},
{
"page": "is_node_relationships",
"title": "Test node relationships",
"topics": [
"is_adjacent",
"is_ancestor",
"is_child",
"is_descendant",
"is_node_relationships",
"is_parent"
]
},
{
"page": "is.tidy_dagitty",
"title": "Test for object class for tidy_dagitty",
"topics": [
"is.tidy_dagitty"
]
},
{
"page": "node_point",
"title": "DAG Nodes",
"topics": [
"geom_dag_node",
"geom_dag_point",
"Nodes"
]
},
{
"page": "paths",
"title": "Find Open Paths Between Variables",
"topics": [
"dag_paths",
"ggdag_paths",
"ggdag_paths_fan",
"Pathways"
]
},
{
"page": "print.tidy_dagitty",
"title": "Print a 'tidy_dagitty'",
"topics": [
"print.tidy_dagitty"
]
},
{
"page": "pull_dag",
"title": "Pull components from DAG objects",
"topics": [
"pull_dag",
"pull_dag.dagitty",
"pull_dag.tidy_dagitty",
"pull_dag_data",
"pull_dag_data.dagitty",
"pull_dag_data.tidy_dagitty",
"update_dag",
"update_dag.tidy_dagitty",
"update_dag<-",
"update_dag<-.tidy_dagitty",
"update_dag_data<-",
"update_dag_data<-.tidy_dagitty"
]
},
{
"page": "query_adjustment_sets",
"title": "Query Adjustment Sets",
"topics": [
"query_adjustment_sets"
]
},
{
"page": "query_ancestors",
"title": "Query Node Ancestors",
"topics": [
"query_ancestors"
]
},
{
"page": "query_children",
"title": "Query Node Children",
"topics": [
"query_children"
]
},
{
"page": "query_colliders",
"title": "Query Collider Nodes",
"topics": [
"query_colliders"
]
},
{
"page": "query_conditional_independence",
"title": "Query and Test Conditional Independence in a DAG",
"topics": [
"ggdag_conditional_independence",
"query_conditional_independence",
"test_conditional_independence"
]
},
{
"page": "query_dconnected",
"title": "Query D-connection",
"topics": [
"query_dconnected"
]
},
{
"page": "query_descendants",
"title": "Query Node Descendants",
"topics": [
"query_descendants"
]
},
{
"page": "query_dseparated",
"title": "Query D-separation",
"topics": [
"query_dseparated"
]
},
{
"page": "query_exogenous",
"title": "Query Exogenous Variables",
"topics": [
"query_exogenous"
]
},
{
"page": "query_instrumental",
"title": "Query Instrumental Variables",
"topics": [
"query_instrumental"
]
},
{
"page": "query_markov_blanket",
"title": "Query Markov Blanket",
"topics": [
"query_markov_blanket"
]
},
{
"page": "query_parents",
"title": "Query Node Parents",
"topics": [
"query_parents"
]
},
{
"page": "query_paths",
"title": "Query Paths in a DAG",
"topics": [
"query_paths"
]
},
{
"page": "query_status",
"title": "Query Variable Status",
"topics": [
"query_status"
]
},
{
"page": "quick_plot",
"title": "Quickly create a DAGs with common structures of bias",
"topics": [
"butterfly_bias",
"collider_triangle",
"confounder_triangle",
"ggdag_butterfly_bias",
"ggdag_collider_triangle",
"ggdag_confounder_triangle",
"ggdag_mediation_triangle",
"ggdag_m_bias",
"ggdag_quartet_collider",
"ggdag_quartet_confounder",
"ggdag_quartet_mediator",
"ggdag_quartet_m_bias",
"ggdag_quartet_time_collider",
"mediation_triangle",
"m_bias",
"quartet_collider",
"quartet_confounder",
"quartet_mediator",
"quartet_m_bias",
"quartet_time_collider",
"Quick Plots for Common DAGs"
]
},
{
"page": "remove_axes",
"title": "Quickly remove plot axes and grids",
"topics": [
"remove_axes",
"remove_grid"
]
},
{
"page": "scale_adjusted",
"title": "Common scale adjustments for DAGs",
"topics": [
"scale_adjusted",
"scale_dag"
]
},
{
"page": "set_curve_edges",
"title": "Set curvature for multiple edges at once",
"topics": [
"set_curve_edges"
]
},
{
"page": "simulate_data",
"title": "Simulate Data from Structural Equation Model",
"topics": [
"simulate_data"
]
},
{
"page": "tbl_df.tidy_dagitty",
"title": "Convert a 'tidy_dagitty' object to tbl_df",
"topics": [
"tbl_df.tidy_dagitty"
]
},
{
"page": "is_collider",
"title": "Detecting colliders in DAGs",
"topics": [
"is_collider",
"is_downstream_collider",
"Test if Variable Is Collider"
]
},
{
"page": "theme_dag_blank",
"title": "Minimalist DAG themes",
"topics": [
"theme_dag",
"theme_dag_blank",
"theme_dag_grid"
]
},
{
"page": "theme_dag_grey",
"title": "Simple grey themes for DAGs",
"topics": [
"theme_dag_gray",
"theme_dag_gray_grid",
"theme_dag_grey",
"theme_dag_grey_grid"
]
},
{
"page": "tidy_dagitty",
"title": "Tidy a 'dagitty' object",
"topics": [
"tidy_dagitty"
]
},
{
"page": "time_ordered_coords",
"title": "Create a time-ordered coordinate data frame",
"topics": [
"time_ordered_coords"
]
},
{
"page": "status",
"title": "Find variable status",
"topics": [
"ggdag_status",
"node_status",
"Variable Status"
]
}
],
"_pkglogo": "https://github.com/r-causal/ggdag/raw/HEAD/man/figures/logo.png",
"_readme": "https://github.com/r-causal/ggdag/raw/HEAD/README.md",
"_rundeps": [
"base64enc",
"boot",
"cachem",
"cli",
"cpp11",
"curl",
"dagitty",
"dplyr",
"farver",
"fastmap",
"forcats",
"generics",
"ggarrow",
"ggforce",
"ggplot2",
"ggraph",
"ggrepel",
"glue",
"graphlayouts",
"gridExtra",
"gtable",
"igraph",
"isoband",
"jsonlite",
"labeling",
"lattice",
"lifecycle",
"magrittr",
"MASS",
"Matrix",
"memoise",
"pillar",
"pkgconfig",
"polyclip",
"purrr",
"R6",
"RColorBrewer",
"Rcpp",
"RcppArmadillo",
"rlang",
"S7",
"scales",
"stringi",
"stringr",
"systemfonts",
"tibble",
"tidygraph",
"tidyr",
"tidyselect",
"tweenr",
"utf8",
"V8",
"vctrs",
"viridis",
"viridisLite",
"withr"
],
"_vignettes": [
{
"source": "intro-to-dags.Rmd",
"filename": "intro-to-dags.html",
"title": "An Introduction to Directed Acyclic Graphs",
"author": "Malcolm Barrett",
"engine": "knitr::rmarkdown",
"headings": [
"Directed Acyclic Graphs",
"Structural Causal Graphs",
"Relationships between variables",
"Colliders and collider-stratification bias",
"Mediation",
"Resources"
],
"created": "2018-03-06 02:48:24",
"modified": "2025-08-10 16:18:31",
"commits": 19
},
{
"source": "intro-to-ggdag.Rmd",
"filename": "intro-to-ggdag.html",
"title": "An Introduction to ggdag",
"author": "Malcolm Barrett",
"engine": "knitr::rmarkdown",
"headings": [
"Overview",
"Creating Directed Acyclic Graphs",
"Working with DAGs",
"Plotting DAGs",
"Plotting directly in ggplot2"
],
"created": "2018-03-06 02:48:24",
"modified": "2025-08-10 16:18:31",
"commits": 16
},
{
"source": "bias-structures.Rmd",
"filename": "bias-structures.html",
"title": "Common Structures of Bias",
"author": "Malcolm Barrett",
"engine": "knitr::rmarkdown",
"headings": [
"Introduction",
"Confounders and confounding",
"Colliders, M-bias, and butterfly bias",
"Measurement error",
"Selection bias",
"Resources"
],
"created": "2018-03-06 02:48:24",
"modified": "2025-08-10 16:18:31",
"commits": 17
}
],
"_score": 13.110722747342956,
"_indexed": true,
"_nocasepkg": "ggdag",
"_universes": [
"r-causal",
"malcolmbarrett"
],
"_binaries": [
{
"r": "4.7.0",
"os": "linux",
"version": "0.2.13.9000",
"date": "2026-05-18T10:04:51.000Z",
"distro": "noble",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "98afaebdc7c4b41676f5c4940f85972327a0ab57d1fcd38e0727493fdec48e8a",
"status": "success",
"check": "OK",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
},
{
"r": "4.6.0",
"os": "linux",
"version": "0.2.13.9000",
"date": "2026-05-18T10:04:35.000Z",
"distro": "noble",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "96b570abd8117f2634b35df76cb8fa6da453ee9dae3452b13a51f3bce15d572a",
"status": "success",
"check": "OK",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
},
{
"r": "4.5.3",
"os": "mac",
"version": "0.2.13.9000",
"date": "2026-05-18T10:04:15.000Z",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "99bee9ca9d942a647b42a38f531c2f150878a8811836a46f95da9de8611d986c",
"status": "success",
"check": "OK",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
},
{
"r": "4.6.0",
"os": "mac",
"version": "0.2.13.9000",
"date": "2026-05-18T10:04:23.000Z",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "cbcbdce0fae06cd8dcee3994a79b985220bc1a129217f1daeb8496f42e928deb",
"status": "success",
"check": "OK",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
},
{
"r": "4.7.0",
"os": "win",
"version": "0.2.13.9000",
"date": "2026-05-18T10:03:52.000Z",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "5824cceeb4904775eea9e39e4b86d51319ba49da2eb39a8a70754d33a603efa8",
"status": "success",
"check": "OK",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
},
{
"r": "4.5.3",
"os": "win",
"version": "0.2.13.9000",
"date": "2026-05-18T10:04:35.000Z",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "4ad89e150135104ba6311dc7fc281d7b5f583f528977f8effa126549ec7fb865",
"status": "success",
"check": "OK",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
},
{
"r": "4.6.0",
"os": "win",
"version": "0.2.13.9000",
"date": "2026-05-18T10:03:51.000Z",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "9e03ee1778d53d9b70b535c825a81d0730069461c681eb978a3332b26157490b",
"status": "success",
"check": "OK",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
},
{
"r": "4.6.0",
"os": "wasm",
"version": "0.2.13.9000",
"date": "2026-06-02T15:55:03.000Z",
"commit": "71997d874337e74eef3f55918b9ac535426f7c4a",
"fileid": "6452db268bd71272b23e31314c9f73cd135c95a57aa112fb8ed012dcb1757c73",
"status": "success",
"buildurl": "https://github.com/r-universe/r-causal/actions/runs/26026521576"
}
]
}