{
  "_id": "6af17fc91c36d7c6403e3062",
  "Package": "tidySEM",
  "Type": "Package",
  "Title": "Tidy Structural Equation Modeling",
  "Version": "0.3.0",
  "Authors@R": "c(person(given = c(\"Caspar\", \"J.\"),\nfamily = \"Van Lissa\",\nrole = c(\"aut\", \"cre\"),\nemail = \"c.j.vanlissa@tilburguniversity.edu\",\ncomment = c(ORCID = \"0000-0002-0808-5024\")),\nperson(given = c(\"Mauricio\"),\nfamily = \"Garnier-Villarreal\",\nrole = c(\"ctb\"),\nemail = \"mgv@pm.me\",\ncomment = c(ORCID = \"0000-0002-2951-6647\")),\nperson(given = c(\"Frank\", \"C\"),\nfamily = \"Gootjes\",\nrole = c(\"ctb\"),\nemail = \"f.c.gootjes@uu.nl\",\ncomment = c(ORCID = \"0000-0002-0639-1001\")) )",
  "Description": "A tidy workflow for generating, estimating, reporting, and\nplotting structural equation models using 'lavaan', 'OpenMx',\nor 'Mplus'. Throughout this workflow, elements of syntax,\nresults, and graphs are represented as 'tidy' data, making them\neasy to customize. Includes functionality to estimate latent\nclass analyses, and to plot 'dagitty' and 'igraph' objects.",
  "License": "GPL (>= 3)",
  "URL": "https://cjvanlissa.github.io/tidySEM/",
  "BugReports": "https://github.com/cjvanlissa/tidySEM/issues",
  "VignetteBuilder": "knitr",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "Roxygen": "list(markdown = TRUE)",
  "Config/roxygen2/version": "8.0.0",
  "Config/pak/sysreqs": "cmake make texlive libicu-dev libssl-dev",
  "Repository": "https://cjvanlissa.r-universe.dev",
  "Date/Publication": "2026-11-09 07:02:44 UTC",
  "RemoteUrl": "https://github.com/cjvanlissa/tidySEM",
  "RemoteRef": "HEAD",
  "RemoteSha": "b6eb160cad950964ccb82652bfc3a33217055923",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-11-09 08:01:00 UTC",
    "User": "root"
  },
  "Author": "Caspar J. Van Lissa [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-0808-5024>),\nMauricio Garnier-Villarreal [ctb] (ORCID:\n<https://orcid.org/0000-0002-2951-6647>),\nFrank C Gootjes [ctb] (ORCID: <https://orcid.org/0000-0002-0639-1001>)",
  "Maintainer": "Caspar J. Van Lissa <c.j.vanlissa@tilburguniversity.edu>",
  "_user": "cjvanlissa",
  "_type": "src",
  "_file": "tidySEM_0.3.0.tar.gz",
  "_fileid": "https://r2.ropensci.org/fc462602f8b82c742698f2195eef33828a6683316bb60583ce2b2009cee87ac9",
  "_filesize": 16038640,
  "_sha256": "fc462602f8b82c742698f2195eef33828a6683316bb60583ce2b2009cee87ac9",
  "_expires": "2027-02-17T08:09:43.000Z",
  "_created": "2026-11-09T08:01:00.000Z",
  "_published": "2026-11-09T08:09:45.477Z",
  "_upstream": "https://github.com/cjvanlissa/tidySEM",
  "_status": "success",
  "_maintainer": {
    "name": "Caspar J. Van Lissa",
    "email": "c.j.vanlissa@tilburguniversity.edu",
    "login": "cjvanlissa",
    "orcid": "0000-0002-0808-5024",
    "description": "Developmental datascientist, studying mothers' and fathers' unique roles in children's socio-emotional development.",
    "uuid": 11941251
  },
  "_jobs": [
    {
      "job": 129046409816,
      "time": 376,
      "config": "linux-devel-x86_64",
      "r": "4.7.0",
      "check": "NOTE",
      "artifact": "13657887796"
    },
    {
      "job": 129046409548,
      "time": 399,
      "config": "linux-release-x86_64",
      "r": "4.6.2",
      "check": "NOTE",
      "artifact": "13658720340"
    },
    {
      "job": 129046409694,
      "time": 334,
      "config": "macos-oldrel-arm64",
      "r": "4.5.3",
      "check": "NOTE",
      "artifact": "13657553697"
    },
    {
      "job": 129046409717,
      "time": 254,
      "config": "macos-release-arm64",
      "r": "4.6.2",
      "check": "NOTE",
      "artifact": "13658196632"
    },
    {
      "job": 129044008851,
      "time": 406,
      "config": "source",
      "r": "4.6.2",
      "check": "OK",
      "artifact": "13658211168"
    },
    {
      "job": 129046409633,
      "time": 214,
      "config": "wasm-release",
      "r": "4.6.0",
      "check": "OK",
      "artifact": "13658550766"
    },
    {
      "job": 129046409690,
      "time": 369,
      "config": "windows-devel-x86_64",
      "r": "4.7.0",
      "check": "NOTE",
      "artifact": "13658476744"
    },
    {
      "job": 129046409653,
      "time": 349,
      "config": "windows-oldrel-x86_64",
      "r": "4.5.3",
      "check": "NOTE",
      "artifact": "13657703396"
    },
    {
      "job": 129046409580,
      "time": 410,
      "config": "windows-release-x86_64",
      "r": "4.6.2",
      "check": "NOTE",
      "artifact": "13657829330"
    }
  ],
  "_buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754",
  "_commit": {
    "id": "b6eb160cad950964ccb82652bfc3a33217055923",
    "author": "yourname <yourname@email.com>",
    "committer": "yourname <yourname@email.com>",
    "message": "update 2026-11-09 08:02:44.480697\n",
    "time": 1794207764
  },
  "_distro": "resolute",
  "_host": "GitHub-Actions",
  "_registered": true,
  "_dependencies": [
    {
      "package": "R",
      "version": ">= 4.0.0",
      "role": "Depends"
    },
    {
      "package": "stats",
      "role": "Depends"
    },
    {
      "package": "utils",
      "role": "Depends"
    },
    {
      "package": "ggplot2",
      "version": ">= 3.5.0",
      "role": "Imports"
    },
    {
      "package": "lavaan",
      "version": ">= 0.6-21",
      "role": "Imports"
    },
    {
      "package": "MplusAutomation",
      "role": "Imports"
    },
    {
      "package": "psych",
      "role": "Imports"
    },
    {
      "package": "methods",
      "role": "Imports"
    },
    {
      "package": "gtable",
      "role": "Imports"
    },
    {
      "package": "dbscan",
      "role": "Imports"
    },
    {
      "package": "RANN",
      "role": "Imports"
    },
    {
      "package": "Matrix",
      "role": "Imports"
    },
    {
      "package": "car",
      "role": "Imports"
    },
    {
      "package": "future.apply",
      "role": "Imports"
    },
    {
      "package": "progressr",
      "role": "Imports"
    },
    {
      "package": "progress",
      "role": "Imports"
    },
    {
      "package": "nonnest2",
      "version": ">= 0.5.6",
      "role": "Imports"
    },
    {
      "package": "testthat",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "dplyr",
      "role": "Suggests"
    },
    {
      "package": "stringr",
      "role": "Suggests"
    },
    {
      "package": "covr",
      "role": "Suggests"
    },
    {
      "package": "tidyLPA",
      "role": "Suggests"
    },
    {
      "package": "poLCA",
      "role": "Suggests"
    },
    {
      "package": "umx",
      "role": "Suggests"
    },
    {
      "package": "mclust",
      "role": "Suggests"
    },
    {
      "package": "MASS",
      "role": "Suggests"
    },
    {
      "package": "scales",
      "role": "Suggests"
    },
    {
      "package": "yaml",
      "role": "Suggests"
    },
    {
      "package": "formatR",
      "role": "Suggests"
    },
    {
      "package": "dagitty",
      "role": "Suggests"
    },
    {
      "package": "mice",
      "role": "Suggests"
    },
    {
      "package": "ggraph",
      "role": "Suggests"
    },
    {
      "package": "OpenMx",
      "version": ">= 2.21.13",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "blavaan",
      "role": "Suggests"
    },
    {
      "package": "bain",
      "role": "Suggests"
    },
    {
      "package": "future",
      "role": "Suggests"
    },
    {
      "package": "igraph",
      "version": ">= 2.0.0",
      "role": "Suggests"
    },
    {
      "package": "broom",
      "role": "Suggests"
    },
    {
      "package": "nnet",
      "role": "Suggests"
    }
  ],
  "_owner": "cjvanlissa",
  "_selfowned": true,
  "_usedby": 4,
  "_updates": [
    {
      "week": "2025-52",
      "n": 4
    },
    {
      "week": "2026-01",
      "n": 9
    },
    {
      "week": "2026-02",
      "n": 4
    },
    {
      "week": "2026-03",
      "n": 2
    },
    {
      "week": "2026-15",
      "n": 4
    },
    {
      "week": "2026-24",
      "n": 1
    },
    {
      "week": "2026-30",
      "n": 2
    },
    {
      "week": "2026-36",
      "n": 5
    },
    {
      "week": "2026-37",
      "n": 1
    },
    {
      "week": "2026-38",
      "n": 1
    },
    {
      "week": "2026-41",
      "n": 6
    },
    {
      "week": "2026-44",
      "n": 12
    },
    {
      "week": "2026-45",
      "n": 8
    },
    {
      "week": "2026-46",
      "n": 1
    }
  ],
  "_tags": [],
  "_stars": 68,
  "_contributors": [
    {
      "user": "cjvanlissa",
      "count": 133,
      "uuid": 11941251
    },
    {
      "user": "opecheese",
      "count": 66,
      "uuid": 71661723
    },
    {
      "user": "gootjes",
      "count": 13,
      "uuid": 37846483
    },
    {
      "user": "foobar123asdf",
      "count": 9,
      "uuid": 35730819
    },
    {
      "user": "maugavilla",
      "count": 9,
      "uuid": 2199544
    },
    {
      "user": "sikoetu",
      "count": 8,
      "uuid": 29733785
    },
    {
      "user": "haozhou1988",
      "count": 3,
      "uuid": 5347702
    },
    {
      "user": "mvuorre",
      "count": 2,
      "uuid": 7349270
    },
    {
      "user": "nx10",
      "count": 1,
      "uuid": 33600480
    }
  ],
  "_userbio": {
    "uuid": 11941251,
    "type": "user",
    "name": "C. J. van Lissa",
    "followers": 126,
    "description": "Developmental datascientist, studying mothers' and fathers' unique roles in children's socio-emotional development."
  },
  "_downloads": {
    "count": 5549,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/tidySEM"
  },
  "_mentions": 1,
  "_devurl": "https://github.com/cjvanlissa/tidysem",
  "_pkgdown": "https://cjvanlissa.github.io/tidySEM/",
  "_searchresults": 477,
  "_rbuild": "4.6.2",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/manual.pdf",
    "extra/tidySEM.html"
  ],
  "_homeurl": "https://github.com/cjvanlissa/tidysem",
  "_realowner": "cjvanlissa",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.1.2",
      "date": "2020-06-25"
    },
    {
      "version": "0.1.3",
      "date": "2020-10-09"
    },
    {
      "version": "0.1.6",
      "date": "2021-02-19"
    },
    {
      "version": "0.1.7",
      "date": "2021-03-11"
    },
    {
      "version": "0.1.8",
      "date": "2021-03-14"
    },
    {
      "version": "0.1.9",
      "date": "2021-04-20"
    },
    {
      "version": "0.1.10",
      "date": "2021-07-13"
    },
    {
      "version": "0.2.0",
      "date": "2021-11-16"
    },
    {
      "version": "0.2.1",
      "date": "2022-02-09"
    },
    {
      "version": "0.2.2",
      "date": "2022-04-06"
    },
    {
      "version": "0.2.3",
      "date": "2022-04-14"
    },
    {
      "version": "0.2.4",
      "date": "2023-05-01"
    },
    {
      "version": "0.2.5",
      "date": "2023-10-10"
    },
    {
      "version": "0.2.6",
      "date": "2023-10-24"
    },
    {
      "version": "0.2.7",
      "date": "2024-06-04"
    },
    {
      "version": "0.2.8",
      "date": "2025-03-04"
    },
    {
      "version": "0.2.9",
      "date": "2025-08-01"
    },
    {
      "version": "0.2.10",
      "date": "2026-01-11"
    },
    {
      "version": "0.2.11",
      "date": "2026-08-20"
    },
    {
      "version": "0.2.12",
      "date": "2026-09-08"
    }
  ],
  "_exports": [
    "add_paths",
    "all_cov",
    "all_fixed",
    "all_fixed_edges",
    "all_fixed_nodes",
    "all_latent",
    "all_load",
    "all_neg",
    "all_neg_edges",
    "all_neg_nodes",
    "all_nonsig",
    "all_nonsig_edges",
    "all_nonsig_nodes",
    "all_obs",
    "all_pos",
    "all_pos_edges",
    "all_pos_nodes",
    "all_reg",
    "all_sig",
    "all_sig_edges",
    "all_sig_nodes",
    "all_var",
    "alpha_cov",
    "alpha_fixed",
    "alpha_fixed_edges",
    "alpha_fixed_nodes",
    "alpha_latent",
    "alpha_load",
    "alpha_neg",
    "alpha_neg_edges",
    "alpha_neg_nodes",
    "alpha_nonsig",
    "alpha_nonsig_edges",
    "alpha_nonsig_nodes",
    "alpha_obs",
    "alpha_pos",
    "alpha_pos_edges",
    "alpha_pos_nodes",
    "alpha_reg",
    "alpha_sig",
    "alpha_sig_edges",
    "alpha_sig_nodes",
    "alpha_var",
    "append_class_draws",
    "as_lavaan",
    "as_mplus",
    "as_ram",
    "BCH",
    "BLRT",
    "chi_sq",
    "chisq_sb",
    "class_prob",
    "color_cov",
    "color_fixed",
    "color_fixed_edges",
    "color_fixed_nodes",
    "color_latent",
    "color_load",
    "color_neg",
    "color_neg_edges",
    "color_neg_nodes",
    "color_nonsig",
    "color_nonsig_edges",
    "color_nonsig_nodes",
    "color_obs",
    "color_pos",
    "color_pos_edges",
    "color_pos_nodes",
    "color_reg",
    "color_sig",
    "color_sig_edges",
    "color_sig_nodes",
    "color_var",
    "colour_cov",
    "colour_fixed",
    "colour_fixed_edges",
    "colour_fixed_nodes",
    "colour_latent",
    "colour_load",
    "colour_neg",
    "colour_neg_edges",
    "colour_neg_nodes",
    "colour_nonsig",
    "colour_nonsig_edges",
    "colour_nonsig_nodes",
    "colour_obs",
    "colour_pos",
    "colour_pos_edges",
    "colour_pos_nodes",
    "colour_reg",
    "colour_sig",
    "colour_sig_edges",
    "colour_sig_nodes",
    "colour_var",
    "conf_int",
    "cors",
    "create_scales",
    "descriptives",
    "deviances_to_thresholds",
    "dictionary",
    "dictionary<-",
    "edges",
    "edges<-",
    "edit_edges",
    "edit_graph",
    "edit_nodes",
    "est_sig",
    "estimate_lavaan",
    "estimate_mplus",
    "estimate_mx",
    "fill_fixed",
    "fill_latent",
    "fill_neg",
    "fill_nonsig",
    "fill_obs",
    "fill_pos",
    "fill_sig",
    "format_numeric",
    "get_data",
    "get_data<-",
    "get_edges",
    "get_estimates",
    "get_fit",
    "get_layout",
    "get_nodes",
    "graph_sem",
    "hide_cov",
    "hide_fixed",
    "hide_fixed_edges",
    "hide_fixed_nodes",
    "hide_latent",
    "hide_load",
    "hide_neg",
    "hide_neg_edges",
    "hide_neg_nodes",
    "hide_nonsig",
    "hide_nonsig_edges",
    "hide_nonsig_nodes",
    "hide_obs",
    "hide_pos",
    "hide_pos_edges",
    "hide_pos_nodes",
    "hide_reg",
    "hide_sig",
    "hide_sig_edges",
    "hide_sig_nodes",
    "hide_var",
    "ic_weights",
    "if_edges",
    "if_edit",
    "if_nodes",
    "label_alpha_cov",
    "label_alpha_fixed",
    "label_alpha_fixed_edges",
    "label_alpha_fixed_nodes",
    "label_alpha_latent",
    "label_alpha_load",
    "label_alpha_neg",
    "label_alpha_neg_edges",
    "label_alpha_neg_nodes",
    "label_alpha_nonsig",
    "label_alpha_nonsig_edges",
    "label_alpha_nonsig_nodes",
    "label_alpha_obs",
    "label_alpha_pos",
    "label_alpha_pos_edges",
    "label_alpha_pos_nodes",
    "label_alpha_reg",
    "label_alpha_sig",
    "label_alpha_sig_edges",
    "label_alpha_sig_nodes",
    "label_alpha_var",
    "label_color_cov",
    "label_color_fixed",
    "label_color_fixed_edges",
    "label_color_fixed_nodes",
    "label_color_latent",
    "label_color_load",
    "label_color_neg",
    "label_color_neg_edges",
    "label_color_neg_nodes",
    "label_color_nonsig",
    "label_color_nonsig_edges",
    "label_color_nonsig_nodes",
    "label_color_obs",
    "label_color_pos",
    "label_color_pos_edges",
    "label_color_pos_nodes",
    "label_color_reg",
    "label_color_sig",
    "label_color_sig_edges",
    "label_color_sig_nodes",
    "label_color_var",
    "label_colour_cov",
    "label_colour_fixed",
    "label_colour_fixed_edges",
    "label_colour_fixed_nodes",
    "label_colour_latent",
    "label_colour_load",
    "label_colour_neg",
    "label_colour_neg_edges",
    "label_colour_neg_nodes",
    "label_colour_nonsig",
    "label_colour_nonsig_edges",
    "label_colour_nonsig_nodes",
    "label_colour_obs",
    "label_colour_pos",
    "label_colour_pos_edges",
    "label_colour_pos_nodes",
    "label_colour_reg",
    "label_colour_sig",
    "label_colour_sig_edges",
    "label_colour_sig_nodes",
    "label_colour_var",
    "label_family_cov",
    "label_family_fixed",
    "label_family_fixed_edges",
    "label_family_fixed_nodes",
    "label_family_latent",
    "label_family_load",
    "label_family_neg",
    "label_family_neg_edges",
    "label_family_neg_nodes",
    "label_family_nonsig",
    "label_family_nonsig_edges",
    "label_family_nonsig_nodes",
    "label_family_obs",
    "label_family_pos",
    "label_family_pos_edges",
    "label_family_pos_nodes",
    "label_family_reg",
    "label_family_sig",
    "label_family_sig_edges",
    "label_family_sig_nodes",
    "label_family_var",
    "label_fill_cov",
    "label_fill_fixed",
    "label_fill_fixed_edges",
    "label_fill_fixed_nodes",
    "label_fill_latent",
    "label_fill_load",
    "label_fill_neg",
    "label_fill_neg_edges",
    "label_fill_neg_nodes",
    "label_fill_nonsig",
    "label_fill_nonsig_edges",
    "label_fill_nonsig_nodes",
    "label_fill_obs",
    "label_fill_pos",
    "label_fill_pos_edges",
    "label_fill_pos_nodes",
    "label_fill_reg",
    "label_fill_sig",
    "label_fill_sig_edges",
    "label_fill_sig_nodes",
    "label_fill_var",
    "label_fontface_cov",
    "label_fontface_fixed",
    "label_fontface_fixed_edges",
    "label_fontface_fixed_nodes",
    "label_fontface_latent",
    "label_fontface_load",
    "label_fontface_neg",
    "label_fontface_neg_edges",
    "label_fontface_neg_nodes",
    "label_fontface_nonsig",
    "label_fontface_nonsig_edges",
    "label_fontface_nonsig_nodes",
    "label_fontface_obs",
    "label_fontface_pos",
    "label_fontface_pos_edges",
    "label_fontface_pos_nodes",
    "label_fontface_reg",
    "label_fontface_sig",
    "label_fontface_sig_edges",
    "label_fontface_sig_nodes",
    "label_fontface_var",
    "label_hjust_cov",
    "label_hjust_fixed",
    "label_hjust_fixed_edges",
    "label_hjust_fixed_nodes",
    "label_hjust_latent",
    "label_hjust_load",
    "label_hjust_neg",
    "label_hjust_neg_edges",
    "label_hjust_neg_nodes",
    "label_hjust_nonsig",
    "label_hjust_nonsig_edges",
    "label_hjust_nonsig_nodes",
    "label_hjust_obs",
    "label_hjust_pos",
    "label_hjust_pos_edges",
    "label_hjust_pos_nodes",
    "label_hjust_reg",
    "label_hjust_sig",
    "label_hjust_sig_edges",
    "label_hjust_sig_nodes",
    "label_hjust_var",
    "label_lineheight_cov",
    "label_lineheight_fixed",
    "label_lineheight_fixed_edges",
    "label_lineheight_fixed_nodes",
    "label_lineheight_latent",
    "label_lineheight_load",
    "label_lineheight_neg",
    "label_lineheight_neg_edges",
    "label_lineheight_neg_nodes",
    "label_lineheight_nonsig",
    "label_lineheight_nonsig_edges",
    "label_lineheight_nonsig_nodes",
    "label_lineheight_obs",
    "label_lineheight_pos",
    "label_lineheight_pos_edges",
    "label_lineheight_pos_nodes",
    "label_lineheight_reg",
    "label_lineheight_sig",
    "label_lineheight_sig_edges",
    "label_lineheight_sig_nodes",
    "label_lineheight_var",
    "label_location_cov",
    "label_location_fixed",
    "label_location_load",
    "label_location_neg",
    "label_location_nonsig",
    "label_location_pos",
    "label_location_reg",
    "label_location_sig",
    "label_size_cov",
    "label_size_fixed",
    "label_size_fixed_edges",
    "label_size_fixed_nodes",
    "label_size_latent",
    "label_size_load",
    "label_size_neg",
    "label_size_neg_edges",
    "label_size_neg_nodes",
    "label_size_nonsig",
    "label_size_nonsig_edges",
    "label_size_nonsig_nodes",
    "label_size_obs",
    "label_size_pos",
    "label_size_pos_edges",
    "label_size_pos_nodes",
    "label_size_reg",
    "label_size_sig",
    "label_size_sig_edges",
    "label_size_sig_nodes",
    "label_size_var",
    "label_vjust_cov",
    "label_vjust_fixed",
    "label_vjust_fixed_edges",
    "label_vjust_fixed_nodes",
    "label_vjust_latent",
    "label_vjust_load",
    "label_vjust_neg",
    "label_vjust_neg_edges",
    "label_vjust_neg_nodes",
    "label_vjust_nonsig",
    "label_vjust_nonsig_edges",
    "label_vjust_nonsig_nodes",
    "label_vjust_obs",
    "label_vjust_pos",
    "label_vjust_pos_edges",
    "label_vjust_pos_nodes",
    "label_vjust_reg",
    "label_vjust_sig",
    "label_vjust_sig_edges",
    "label_vjust_sig_nodes",
    "label_vjust_var",
    "linetype_cov",
    "linetype_fixed",
    "linetype_fixed_edges",
    "linetype_fixed_nodes",
    "linetype_latent",
    "linetype_load",
    "linetype_neg",
    "linetype_neg_edges",
    "linetype_neg_nodes",
    "linetype_nonsig",
    "linetype_nonsig_edges",
    "linetype_nonsig_nodes",
    "linetype_obs",
    "linetype_pos",
    "linetype_pos_edges",
    "linetype_pos_nodes",
    "linetype_reg",
    "linetype_sig",
    "linetype_sig_edges",
    "linetype_sig_nodes",
    "linetype_var",
    "lr_lmr",
    "lr_test",
    "lsub",
    "measurement",
    "mixture_starts",
    "mplus_expand_names",
    "mx_data_quantiles",
    "mx_deviances",
    "mx_diagnostics",
    "mx_dummies",
    "mx_growth_mixture",
    "mx_lca",
    "mx_mixed_lca",
    "mx_mixture",
    "mx_profiles",
    "mx_switch_labels",
    "nodes",
    "nodes<-",
    "one_step",
    "paste2",
    "plot_bivariate",
    "plot_density",
    "plot_growth",
    "plot_prob",
    "plot_profiles",
    "pmc",
    "pmc_srmr",
    "poms",
    "predict_class",
    "prepare_graph",
    "pseudo_class",
    "random_starts",
    "register_tidySEM_method",
    "report",
    "run_lavaan",
    "run_mx",
    "show_cov",
    "show_fixed",
    "show_fixed_edges",
    "show_fixed_nodes",
    "show_latent",
    "show_load",
    "show_neg",
    "show_neg_edges",
    "show_neg_nodes",
    "show_nonsig",
    "show_nonsig_edges",
    "show_nonsig_nodes",
    "show_obs",
    "show_pos",
    "show_pos_edges",
    "show_pos_nodes",
    "show_reg",
    "show_sig",
    "show_sig_edges",
    "show_sig_nodes",
    "show_var",
    "size_cov",
    "size_fixed",
    "size_fixed_edges",
    "size_fixed_nodes",
    "size_latent",
    "size_load",
    "size_neg",
    "size_neg_edges",
    "size_neg_nodes",
    "size_nonsig",
    "size_nonsig_edges",
    "size_nonsig_nodes",
    "size_obs",
    "size_pos",
    "size_pos_edges",
    "size_pos_nodes",
    "size_reg",
    "size_sig",
    "size_sig_edges",
    "size_sig_nodes",
    "size_var",
    "skew_kurtosis",
    "srmr",
    "syntax",
    "syntax<-",
    "table_cors",
    "table_fit",
    "table_prob",
    "table_results",
    "tidy_sem",
    "two_step",
    "wald_test"
  ],
  "_datasets": [
    {
      "name": "alkema_microplastics",
      "title": "Ocean Microplastics Data",
      "object": "alkema_microplastics",
      "class": [
        "data.frame"
      ],
      "fields": [
        "current",
        "sample",
        "length",
        "width",
        "height_est",
        "height_obs",
        "category",
        "poly_type",
        "two_dim",
        "film",
        "line"
      ],
      "rows": 6942,
      "table": true,
      "tojson": true
    },
    {
      "name": "curry_mac",
      "title": "Simulated MAC data",
      "object": "curry_mac",
      "class": [
        "data.frame"
      ],
      "fields": [
        "sex",
        "age_years",
        "KinshipR",
        "MutualismR",
        "ExchangeR",
        "HawkR",
        "DoveR",
        "DivisionR",
        "PossessionR",
        "KinshipJ",
        "MutualismJ",
        "ExchangeJ",
        "HawkJ",
        "DoveJ",
        "DivisionJ",
        "PossessionJ"
      ],
      "rows": 1392,
      "table": true,
      "tojson": true
    },
    {
      "name": "data_mix_ordinal",
      "title": "Simulated data for mixture model with ordinal indicators",
      "object": "data_mix_ordinal",
      "class": [
        "data.frame"
      ],
      "fields": [
        "u1",
        "u2",
        "u3",
        "u4"
      ],
      "rows": 5000,
      "table": true,
      "tojson": true
    },
    {
      "name": "empathy",
      "title": "Simulated empathy data",
      "object": "empathy",
      "class": [
        "data.frame"
      ],
      "fields": [
        "ec1",
        "ec2",
        "ec3",
        "ec4",
        "ec5",
        "ec6",
        "pt1",
        "pt2",
        "pt3",
        "pt4",
        "pt5",
        "pt6",
        "sex"
      ],
      "rows": 467,
      "table": true,
      "tojson": true
    },
    {
      "name": "maene_identity",
      "title": "National Identity, Discrimination and Depression",
      "object": "maene_identity",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Ethnic_1",
        "Ethnic_2",
        "Ethnic_3",
        "Belgian",
        "Flemish",
        "age",
        "sex",
        "ses",
        "belgianborn",
        "age_belgium",
        "vict_bully",
        "vict_teacher",
        "depression"
      ],
      "rows": 439,
      "table": true,
      "tojson": true
    },
    {
      "name": "plas_depression",
      "title": "Simulated depression data",
      "object": "plas_depression",
      "class": [
        "data.frame"
      ],
      "fields": [
        "scl.1",
        "scl.2",
        "scl.3",
        "scl.4",
        "scl.5",
        "scl.6"
      ],
      "rows": 978,
      "table": true,
      "tojson": true
    },
    {
      "name": "zegwaard_carecompass",
      "title": "Caregiver Compass Data",
      "object": "zegwaard_carecompass",
      "class": [
        "data.frame"
      ],
      "fields": [
        "burdened",
        "trapped",
        "negaffect",
        "loneliness",
        "sex",
        "sexpatient",
        "cohabiting",
        "distance",
        "freqvisit",
        "relationship"
      ],
      "rows": 513,
      "table": true,
      "tojson": true
    },
    {
      "name": "zhao_2025",
      "title": "Academic Stress, Motivation, and Exercise Behavior",
      "object": "zhao_2025",
      "class": [
        "data.frame"
      ],
      "fields": [
        "ID",
        "Grade",
        "Age",
        "Gender",
        "TS1",
        "TS2",
        "TS3",
        "TS4",
        "SOS1",
        "SOS2",
        "SOS3",
        "SOS4",
        "PS1",
        "PS2",
        "PS3",
        "PS4",
        "PS5",
        "AM1",
        "AM2",
        "AM3",
        "AM4",
        "AM5",
        "CM1",
        "CM2",
        "CM3",
        "CM4",
        "BI1",
        "BI2",
        "BI3",
        "BH1",
        "BH2"
      ],
      "rows": 291,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "add_paths",
      "title": "Add paths to an object of class 'tidy_sem'",
      "topics": [
        "add_paths"
      ]
    },
    {
      "page": "alkema_microplastics",
      "title": "Ocean Microplastics Data",
      "topics": [
        "alkema_microplastics"
      ]
    },
    {
      "page": "append_class_draws",
      "title": "Append Pseudo-class Draws",
      "topics": [
        "append_class_draws"
      ]
    },
    {
      "page": "as_lavaan",
      "title": "Convert tidy_sem to 'lavaan' syntax",
      "topics": [
        "as_lavaan"
      ]
    },
    {
      "page": "as_mplus",
      "title": "Convert tidy_sem to 'Mplus' syntax",
      "topics": [
        "as_mplus"
      ]
    },
    {
      "page": "as_ram",
      "title": "Convert lavaan syntax to RAM specification",
      "topics": [
        "as_ram",
        "as_ram.data.frame"
      ]
    },
    {
      "page": "BCH",
      "title": "Estimate an Auxiliary Model using the BCH Method",
      "topics": [
        "BCH"
      ]
    },
    {
      "page": "BLRT",
      "title": "Conduct Bootstrapped Likelihood Ratio Test",
      "topics": [
        "BLRT"
      ]
    },
    {
      "page": "chi_sq",
      "title": "Calculate Chi Square Statistic",
      "topics": [
        "chi_sq"
      ]
    },
    {
      "page": "class_prob",
      "title": "Obtain latent class probabilities",
      "topics": [
        "class_prob"
      ]
    },
    {
      "page": "conf_int",
      "title": "Format confidence intervals",
      "concept": [
        "Reporting tools"
      ],
      "topics": [
        "conf_int"
      ]
    },
    {
      "page": "cors",
      "title": "Generate syntax for correlations",
      "topics": [
        "cors"
      ]
    },
    {
      "page": "create_scales",
      "title": "Create scale scores from observed variables",
      "topics": [
        "create_scales",
        "create_scales.tidy_sem"
      ]
    },
    {
      "page": "curry_mac",
      "title": "Simulated MAC data",
      "topics": [
        "curry_mac"
      ]
    },
    {
      "page": "data_mix_ordinal",
      "title": "Simulated data for mixture model with ordinal indicators",
      "topics": [
        "data_mix_ordinal"
      ]
    },
    {
      "page": "descriptives",
      "title": "Describe a dataset",
      "topics": [
        "descriptives"
      ]
    },
    {
      "page": "deviances_to_thresholds",
      "title": "Convert deviances to thresholds",
      "topics": [
        "deviances_to_thresholds"
      ]
    },
    {
      "page": "dictionary",
      "title": "Extract dictionary from tidy_sem",
      "topics": [
        "dictionary",
        "dictionary<-"
      ]
    },
    {
      "page": "edges",
      "title": "Extract edges from sem_graph",
      "topics": [
        "edges",
        "edges<-"
      ]
    },
    {
      "page": "edit_graph",
      "title": "Edit graph elements",
      "topics": [
        "edit_edges",
        "edit_graph",
        "edit_nodes"
      ]
    },
    {
      "page": "empathy",
      "title": "Simulated empathy data",
      "topics": [
        "empathy"
      ]
    },
    {
      "page": "est_sig",
      "title": "Add significance asterisks to object",
      "concept": [
        "Reporting tools"
      ],
      "topics": [
        "est_sig"
      ]
    },
    {
      "page": "estimate_lavaan",
      "title": "Estimate tidy_sem using 'lavaan'",
      "topics": [
        "estimate_lavaan"
      ]
    },
    {
      "page": "estimate_mplus",
      "title": "Estimate tidy_sem using 'Mplus'",
      "topics": [
        "estimate_mplus"
      ]
    },
    {
      "page": "estimate_mx",
      "title": "Estimate tidy_sem using 'OpenMx'",
      "topics": [
        "estimate_mx"
      ]
    },
    {
      "page": "format_numeric",
      "title": "Format numeric columns Formats the numeric columns of a data.frame, to round to a specific number of digits.",
      "topics": [
        "format_numeric"
      ]
    },
    {
      "page": "get_data",
      "title": "Extract data from tidy_sem",
      "topics": [
        "get_data",
        "get_data<-"
      ]
    },
    {
      "page": "get_edges",
      "title": "Extract edges from a SEM model object",
      "topics": [
        "get_edges"
      ]
    },
    {
      "page": "get_fit",
      "title": "Get fit indices from objects",
      "topics": [
        "get_fit"
      ]
    },
    {
      "page": "get_layout",
      "title": "Generate graph layout",
      "topics": [
        "get_layout",
        "get_layout.default",
        "get_layout.lavaan"
      ]
    },
    {
      "page": "get_nodes",
      "title": "Extract nodes from a SEM model object",
      "topics": [
        "get_nodes"
      ]
    },
    {
      "page": "graph_sem",
      "title": "Render a graph",
      "topics": [
        "graph_sem",
        "graph_sem.character",
        "graph_sem.dagitty",
        "graph_sem.default",
        "graph_sem.igraph",
        "graph_sem.lavaan",
        "graph_sem.mplus.model",
        "graph_sem.mplusObject",
        "graph_sem.MxModel"
      ]
    },
    {
      "page": "ic_weights",
      "title": "Compare Information Criteria",
      "topics": [
        "ic_weights"
      ]
    },
    {
      "page": "if_edit",
      "title": "Conditionally edit a sem_graph object",
      "topics": [
        "all_cov",
        "all_fixed",
        "all_fixed_edges",
        "all_fixed_nodes",
        "all_latent",
        "all_load",
        "all_neg",
        "all_neg_edges",
        "all_neg_nodes",
        "all_nonsig",
        "all_nonsig_edges",
        "all_nonsig_nodes",
        "all_obs",
        "all_pos",
        "all_pos_edges",
        "all_pos_nodes",
        "all_reg",
        "all_sig",
        "all_sig_edges",
        "all_sig_nodes",
        "all_var",
        "alpha_cov",
        "alpha_fixed",
        "alpha_fixed_edges",
        "alpha_fixed_nodes",
        "alpha_latent",
        "alpha_load",
        "alpha_neg",
        "alpha_neg_edges",
        "alpha_neg_nodes",
        "alpha_nonsig",
        "alpha_nonsig_edges",
        "alpha_nonsig_nodes",
        "alpha_obs",
        "alpha_pos",
        "alpha_pos_edges",
        "alpha_pos_nodes",
        "alpha_reg",
        "alpha_sig",
        "alpha_sig_edges",
        "alpha_sig_nodes",
        "alpha_var",
        "color_cov",
        "color_fixed",
        "color_fixed_edges",
        "color_fixed_nodes",
        "color_latent",
        "color_load",
        "color_neg",
        "color_neg_edges",
        "color_neg_nodes",
        "color_nonsig",
        "color_nonsig_edges",
        "color_nonsig_nodes",
        "color_obs",
        "color_pos",
        "color_pos_edges",
        "color_pos_nodes",
        "color_reg",
        "color_sig",
        "color_sig_edges",
        "color_sig_nodes",
        "color_var",
        "colour_cov",
        "colour_fixed",
        "colour_fixed_edges",
        "colour_fixed_nodes",
        "colour_latent",
        "colour_load",
        "colour_neg",
        "colour_neg_edges",
        "colour_neg_nodes",
        "colour_nonsig",
        "colour_nonsig_edges",
        "colour_nonsig_nodes",
        "colour_obs",
        "colour_pos",
        "colour_pos_edges",
        "colour_pos_nodes",
        "colour_reg",
        "colour_sig",
        "colour_sig_edges",
        "colour_sig_nodes",
        "colour_var",
        "fill_fixed",
        "fill_latent",
        "fill_neg",
        "fill_nonsig",
        "fill_obs",
        "fill_pos",
        "fill_sig",
        "hide_cov",
        "hide_fixed",
        "hide_fixed_edges",
        "hide_fixed_nodes",
        "hide_latent",
        "hide_load",
        "hide_neg",
        "hide_neg_edges",
        "hide_neg_nodes",
        "hide_nonsig",
        "hide_nonsig_edges",
        "hide_nonsig_nodes",
        "hide_obs",
        "hide_pos",
        "hide_pos_edges",
        "hide_pos_nodes",
        "hide_reg",
        "hide_sig",
        "hide_sig_edges",
        "hide_sig_nodes",
        "hide_var",
        "if_edges",
        "if_edit",
        "if_edit.sem_graph",
        "if_nodes",
        "label_alpha_cov",
        "label_alpha_fixed",
        "label_alpha_fixed_edges",
        "label_alpha_fixed_nodes",
        "label_alpha_latent",
        "label_alpha_load",
        "label_alpha_neg",
        "label_alpha_neg_edges",
        "label_alpha_neg_nodes",
        "label_alpha_nonsig",
        "label_alpha_nonsig_edges",
        "label_alpha_nonsig_nodes",
        "label_alpha_obs",
        "label_alpha_pos",
        "label_alpha_pos_edges",
        "label_alpha_pos_nodes",
        "label_alpha_reg",
        "label_alpha_sig",
        "label_alpha_sig_edges",
        "label_alpha_sig_nodes",
        "label_alpha_var",
        "label_color_cov",
        "label_color_fixed",
        "label_color_fixed_edges",
        "label_color_fixed_nodes",
        "label_color_latent",
        "label_color_load",
        "label_color_neg",
        "label_color_neg_edges",
        "label_color_neg_nodes",
        "label_color_nonsig",
        "label_color_nonsig_edges",
        "label_color_nonsig_nodes",
        "label_color_obs",
        "label_color_pos",
        "label_color_pos_edges",
        "label_color_pos_nodes",
        "label_color_reg",
        "label_color_sig",
        "label_color_sig_edges",
        "label_color_sig_nodes",
        "label_color_var",
        "label_colour_cov",
        "label_colour_fixed",
        "label_colour_fixed_edges",
        "label_colour_fixed_nodes",
        "label_colour_latent",
        "label_colour_load",
        "label_colour_neg",
        "label_colour_neg_edges",
        "label_colour_neg_nodes",
        "label_colour_nonsig",
        "label_colour_nonsig_edges",
        "label_colour_nonsig_nodes",
        "label_colour_obs",
        "label_colour_pos",
        "label_colour_pos_edges",
        "label_colour_pos_nodes",
        "label_colour_reg",
        "label_colour_sig",
        "label_colour_sig_edges",
        "label_colour_sig_nodes",
        "label_colour_var",
        "label_family_cov",
        "label_family_fixed",
        "label_family_fixed_edges",
        "label_family_fixed_nodes",
        "label_family_latent",
        "label_family_load",
        "label_family_neg",
        "label_family_neg_edges",
        "label_family_neg_nodes",
        "label_family_nonsig",
        "label_family_nonsig_edges",
        "label_family_nonsig_nodes",
        "label_family_obs",
        "label_family_pos",
        "label_family_pos_edges",
        "label_family_pos_nodes",
        "label_family_reg",
        "label_family_sig",
        "label_family_sig_edges",
        "label_family_sig_nodes",
        "label_family_var",
        "label_fill_cov",
        "label_fill_fixed",
        "label_fill_fixed_edges",
        "label_fill_fixed_nodes",
        "label_fill_latent",
        "label_fill_load",
        "label_fill_neg",
        "label_fill_neg_edges",
        "label_fill_neg_nodes",
        "label_fill_nonsig",
        "label_fill_nonsig_edges",
        "label_fill_nonsig_nodes",
        "label_fill_obs",
        "label_fill_pos",
        "label_fill_pos_edges",
        "label_fill_pos_nodes",
        "label_fill_reg",
        "label_fill_sig",
        "label_fill_sig_edges",
        "label_fill_sig_nodes",
        "label_fill_var",
        "label_fontface_cov",
        "label_fontface_fixed",
        "label_fontface_fixed_edges",
        "label_fontface_fixed_nodes",
        "label_fontface_latent",
        "label_fontface_load",
        "label_fontface_neg",
        "label_fontface_neg_edges",
        "label_fontface_neg_nodes",
        "label_fontface_nonsig",
        "label_fontface_nonsig_edges",
        "label_fontface_nonsig_nodes",
        "label_fontface_obs",
        "label_fontface_pos",
        "label_fontface_pos_edges",
        "label_fontface_pos_nodes",
        "label_fontface_reg",
        "label_fontface_sig",
        "label_fontface_sig_edges",
        "label_fontface_sig_nodes",
        "label_fontface_var",
        "label_hjust_cov",
        "label_hjust_fixed",
        "label_hjust_fixed_edges",
        "label_hjust_fixed_nodes",
        "label_hjust_latent",
        "label_hjust_load",
        "label_hjust_neg",
        "label_hjust_neg_edges",
        "label_hjust_neg_nodes",
        "label_hjust_nonsig",
        "label_hjust_nonsig_edges",
        "label_hjust_nonsig_nodes",
        "label_hjust_obs",
        "label_hjust_pos",
        "label_hjust_pos_edges",
        "label_hjust_pos_nodes",
        "label_hjust_reg",
        "label_hjust_sig",
        "label_hjust_sig_edges",
        "label_hjust_sig_nodes",
        "label_hjust_var",
        "label_lineheight_cov",
        "label_lineheight_fixed",
        "label_lineheight_fixed_edges",
        "label_lineheight_fixed_nodes",
        "label_lineheight_latent",
        "label_lineheight_load",
        "label_lineheight_neg",
        "label_lineheight_neg_edges",
        "label_lineheight_neg_nodes",
        "label_lineheight_nonsig",
        "label_lineheight_nonsig_edges",
        "label_lineheight_nonsig_nodes",
        "label_lineheight_obs",
        "label_lineheight_pos",
        "label_lineheight_pos_edges",
        "label_lineheight_pos_nodes",
        "label_lineheight_reg",
        "label_lineheight_sig",
        "label_lineheight_sig_edges",
        "label_lineheight_sig_nodes",
        "label_lineheight_var",
        "label_location_cov",
        "label_location_fixed",
        "label_location_load",
        "label_location_neg",
        "label_location_nonsig",
        "label_location_pos",
        "label_location_reg",
        "label_location_sig",
        "label_size_cov",
        "label_size_fixed",
        "label_size_fixed_edges",
        "label_size_fixed_nodes",
        "label_size_latent",
        "label_size_load",
        "label_size_neg",
        "label_size_neg_edges",
        "label_size_neg_nodes",
        "label_size_nonsig",
        "label_size_nonsig_edges",
        "label_size_nonsig_nodes",
        "label_size_obs",
        "label_size_pos",
        "label_size_pos_edges",
        "label_size_pos_nodes",
        "label_size_reg",
        "label_size_sig",
        "label_size_sig_edges",
        "label_size_sig_nodes",
        "label_size_var",
        "label_vjust_cov",
        "label_vjust_fixed",
        "label_vjust_fixed_edges",
        "label_vjust_fixed_nodes",
        "label_vjust_latent",
        "label_vjust_load",
        "label_vjust_neg",
        "label_vjust_neg_edges",
        "label_vjust_neg_nodes",
        "label_vjust_nonsig",
        "label_vjust_nonsig_edges",
        "label_vjust_nonsig_nodes",
        "label_vjust_obs",
        "label_vjust_pos",
        "label_vjust_pos_edges",
        "label_vjust_pos_nodes",
        "label_vjust_reg",
        "label_vjust_sig",
        "label_vjust_sig_edges",
        "label_vjust_sig_nodes",
        "label_vjust_var",
        "linetype_cov",
        "linetype_fixed",
        "linetype_fixed_edges",
        "linetype_fixed_nodes",
        "linetype_latent",
        "linetype_load",
        "linetype_neg",
        "linetype_neg_edges",
        "linetype_neg_nodes",
        "linetype_nonsig",
        "linetype_nonsig_edges",
        "linetype_nonsig_nodes",
        "linetype_obs",
        "linetype_pos",
        "linetype_pos_edges",
        "linetype_pos_nodes",
        "linetype_reg",
        "linetype_sig",
        "linetype_sig_edges",
        "linetype_sig_nodes",
        "linetype_var",
        "show_cov",
        "show_fixed",
        "show_fixed_edges",
        "show_fixed_nodes",
        "show_latent",
        "show_load",
        "show_neg",
        "show_neg_edges",
        "show_neg_nodes",
        "show_nonsig",
        "show_nonsig_edges",
        "show_nonsig_nodes",
        "show_obs",
        "show_pos",
        "show_pos_edges",
        "show_pos_nodes",
        "show_reg",
        "show_sig",
        "show_sig_edges",
        "show_sig_nodes",
        "show_var",
        "size_cov",
        "size_fixed",
        "size_fixed_edges",
        "size_fixed_nodes",
        "size_latent",
        "size_load",
        "size_neg",
        "size_neg_edges",
        "size_neg_nodes",
        "size_nonsig",
        "size_nonsig_edges",
        "size_nonsig_nodes",
        "size_obs",
        "size_pos",
        "size_pos_edges",
        "size_pos_nodes",
        "size_reg",
        "size_sig",
        "size_sig_edges",
        "size_sig_nodes",
        "size_var"
      ]
    },
    {
      "page": "lr_lmr",
      "title": "Lo-Mendell-Rubin Likelihood Ratio Test",
      "topics": [
        "lr_lmr"
      ]
    },
    {
      "page": "lr_test",
      "title": "Conduct Likelihood Ratio tests",
      "topics": [
        "lr_test"
      ]
    },
    {
      "page": "lsub",
      "title": "Apply pattern replacement over a vector",
      "topics": [
        "lsub"
      ]
    },
    {
      "page": "maene_identity",
      "title": "National Identity, Discrimination and Depression",
      "topics": [
        "maene_identity"
      ]
    },
    {
      "page": "measurement",
      "title": "Generate syntax for a measurement model",
      "topics": [
        "measurement"
      ]
    },
    {
      "page": "mixture_starts",
      "title": "Automatically set starting values for an OpenMx mixture model",
      "topics": [
        "mixture_starts"
      ]
    },
    {
      "page": "mplus_expand_names",
      "title": "Expand abbreviated Mplus variable names",
      "topics": [
        "mplus_expand_names"
      ]
    },
    {
      "page": "mx_data_quantiles",
      "title": "Data Quantiles",
      "topics": [
        "mx_data_quantiles"
      ]
    },
    {
      "page": "mx_deviances",
      "title": "Create Thresholds Based on Deviances",
      "topics": [
        "mx_deviances"
      ]
    },
    {
      "page": "mx_diagnostics",
      "title": "Diagnose an 'OpenMx' Model",
      "topics": [
        "mx_diagnostics"
      ]
    },
    {
      "page": "mx_dummies",
      "title": "Dummy Code Factor Variables",
      "topics": [
        "mx_dummies"
      ]
    },
    {
      "page": "mx_growth_mixture",
      "title": "Estimate growth mixture models using OpenMx",
      "topics": [
        "mx_growth_mixture"
      ]
    },
    {
      "page": "mx_lca",
      "title": "Estimate latent class analyses using OpenMx",
      "topics": [
        "mx_lca"
      ]
    },
    {
      "page": "mx_mixed_lca",
      "title": "Estimate mixed data latent class analysis using OpenMx",
      "topics": [
        "mx_mixed_lca"
      ]
    },
    {
      "page": "mx_mixture",
      "title": "Estimate mixture models using OpenMx",
      "topics": [
        "mx_mixture"
      ]
    },
    {
      "page": "mx_profiles",
      "title": "Estimate latent profile analyses using OpenMx",
      "topics": [
        "mx_profiles"
      ]
    },
    {
      "page": "mx_switch_labels",
      "title": "Switch LCA Class Labels",
      "topics": [
        "mx_switch_labels"
      ]
    },
    {
      "page": "nodes",
      "title": "Extract nodes from sem_graph",
      "topics": [
        "nodes",
        "nodes<-"
      ]
    },
    {
      "page": "one_step",
      "title": "One-Step Method for Auxiliary Analysis",
      "topics": [
        "one_step"
      ]
    },
    {
      "page": "paste2",
      "title": "Concatenate Strings while omitting NA",
      "topics": [
        "paste2"
      ]
    },
    {
      "page": "plas_depression",
      "title": "Simulated depression data",
      "topics": [
        "plas_depression"
      ]
    },
    {
      "page": "plot_bivariate",
      "title": "Create correlation plots for a mixture model",
      "topics": [
        "plot_bivariate"
      ]
    },
    {
      "page": "plot_density",
      "title": "Create density plots for mixture models",
      "topics": [
        "plot_density"
      ]
    },
    {
      "page": "plot_prob",
      "title": "Plot categorical variable probabilities",
      "topics": [
        "plot_prob"
      ]
    },
    {
      "page": "plot_profiles",
      "title": "Create latent profile plots",
      "topics": [
        "plot_profiles",
        "plot_profiles.default"
      ]
    },
    {
      "page": "pmc",
      "title": "Predictive Model Comparison",
      "topics": [
        "pmc",
        "pmc_srmr"
      ]
    },
    {
      "page": "predict_class",
      "title": "Predict Class Membership",
      "topics": [
        "predict_class"
      ]
    },
    {
      "page": "prepare_graph",
      "title": "Prepare graph data",
      "topics": [
        "prepare_graph",
        "prepare_graph.character",
        "prepare_graph.dagitty",
        "prepare_graph.default",
        "prepare_graph.lavaan",
        "prepare_graph.mplus.model",
        "prepare_graph.mplusObject",
        "prepare_graph.MxModel"
      ]
    },
    {
      "page": "pseudo_class",
      "title": "Estimate an Auxiliary Model using the Pseudo-Class Method",
      "topics": [
        "pseudo_class",
        "pseudo_class.MxModel"
      ]
    },
    {
      "page": "random_starts",
      "title": "Generate Random Starting Values for OpenMx Models",
      "topics": [
        "random_starts",
        "random_starts_internal_mixture"
      ]
    },
    {
      "page": "register_tidySEM_method",
      "title": "Register an External tidySEM Method",
      "topics": [
        "register_tidySEM_method"
      ]
    },
    {
      "page": "run_lavaan",
      "title": "Run as lavaan model",
      "topics": [
        "run_lavaan"
      ]
    },
    {
      "page": "run_mx",
      "title": "Run as OpenMx model with sensible defaults",
      "topics": [
        "run_mx"
      ]
    },
    {
      "page": "skew_kurtosis",
      "title": "Calculate skew and kurtosis",
      "topics": [
        "skew_kurtosis"
      ]
    },
    {
      "page": "srmr",
      "title": "Calculate Standardized Root Mean Residual",
      "topics": [
        "srmr"
      ]
    },
    {
      "page": "syntax",
      "title": "Extract syntax from tidy_sem",
      "topics": [
        "syntax",
        "syntax<-"
      ]
    },
    {
      "page": "table_cors",
      "title": "Extract correlation tables",
      "topics": [
        "table_cors"
      ]
    },
    {
      "page": "table_fit",
      "title": "Print model fit table formatted for publication",
      "concept": [
        "Reporting tools"
      ],
      "topics": [
        "table_fit"
      ]
    },
    {
      "page": "table_prob",
      "title": "Results table in probability scale",
      "concept": [
        "Reporting tools"
      ],
      "topics": [
        "table_prob"
      ]
    },
    {
      "page": "table_results",
      "title": "Print results table formatted for publication",
      "concept": [
        "Reporting tools"
      ],
      "topics": [
        "table_results"
      ]
    },
    {
      "page": "tidy_sem",
      "title": "Create a tidy_sem object",
      "topics": [
        "tidy_sem"
      ]
    },
    {
      "page": "two_step",
      "title": "Estimate an Auxiliary Model Using Two-Step Maximum Likelihood",
      "topics": [
        "two_step"
      ]
    },
    {
      "page": "wald_test",
      "title": "Wald Test for Linear Hypotheses",
      "topics": [
        "wald_test"
      ]
    },
    {
      "page": "zegwaard_carecompass",
      "title": "Caregiver Compass Data",
      "topics": [
        "zegwaard_carecompass"
      ]
    },
    {
      "page": "zhao_2025",
      "title": "Academic Stress, Motivation, and Exercise Behavior",
      "topics": [
        "zhao_2025"
      ]
    }
  ],
  "_rundeps": [
    "abind",
    "askpass",
    "backports",
    "boot",
    "broom",
    "car",
    "carData",
    "checkmate",
    "cli",
    "coda",
    "codetools",
    "colorspace",
    "CompQuadForm",
    "cowplot",
    "cpp11",
    "crayon",
    "curl",
    "data.table",
    "dbscan",
    "Deriv",
    "digest",
    "doBy",
    "dplyr",
    "farver",
    "fastDummies",
    "forecast",
    "Formula",
    "fracdiff",
    "future",
    "future.apply",
    "generics",
    "ggplot2",
    "globals",
    "glue",
    "GPArotation",
    "gsubfn",
    "gtable",
    "hms",
    "httr",
    "isoband",
    "jsonlite",
    "labeling",
    "lattice",
    "lavaan",
    "lifecycle",
    "listenv",
    "lme4",
    "lmtest",
    "magrittr",
    "MASS",
    "Matrix",
    "MatrixModels",
    "mgcv",
    "mime",
    "minqa",
    "mnormt",
    "modelr",
    "MplusAutomation",
    "mvtnorm",
    "nlme",
    "nloptr",
    "nnet",
    "nonnest2",
    "numDeriv",
    "openssl",
    "pander",
    "parallelly",
    "pbivnorm",
    "pbkrtest",
    "pillar",
    "pkgconfig",
    "plyr",
    "prettyunits",
    "progress",
    "progressr",
    "proto",
    "psych",
    "purrr",
    "quadprog",
    "quantreg",
    "R6",
    "RANN",
    "rbibutils",
    "RColorBrewer",
    "Rcpp",
    "RcppArmadillo",
    "RcppEigen",
    "Rdpack",
    "reformulas",
    "rlang",
    "S7",
    "sandwich",
    "scales",
    "SparseM",
    "stringi",
    "stringr",
    "survival",
    "sys",
    "texreg",
    "tibble",
    "tidyr",
    "tidyselect",
    "timeDate",
    "urca",
    "utf8",
    "vctrs",
    "viridisLite",
    "withr",
    "xtable",
    "zoo"
  ],
  "_vignettes": [
    {
      "source": "lca_auxiliary.Rmd",
      "filename": "lca_auxiliary.html",
      "title": "Auxiliary Analyses for Latent Classes",
      "engine": "knitr::rmarkdown",
      "headings": [
        "The Naive Approach",
        "Example: Caregiver profiles",
        "Classification uncertainty",
        "BCH: class differences in distal outcomes",
        "Continuous distal outcome",
        "Binary or ordinal distal outcome",
        "A class-specific regression model",
        "Two-step maximum likelihood",
        "Pseudo-class draws and pooling",
        "Compare distal means",
        "Use RAM syntax",
        "Predicting class membership",
        "Reporting auxiliary analyses"
      ],
      "created": "2026-11-07 16:44:49",
      "modified": "2026-11-08 09:52:47",
      "commits": 2
    },
    {
      "source": "lca_confirmatory.Rmd",
      "filename": "lca_confirmatory.html",
      "title": "Confirmatory Latent Class Analysis",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Example 1: Depression",
        "Simulate example data",
        "Test the number of classes",
        "Translate theoretical assumptions into parameter constraints",
        "Example 2: Caregiver Compass",
        "Loading the Data",
        "Descriptive statistics",
        "Conducting Latent Profile Analysis",
        "Class Enumeration",
        "Using ICs",
        "Using LMR tests",
        "Using BLRT tests",
        "Optional: Alternative Model Specifications",
        "Interpreting the Final Class Solution",
        "Predicting class membership"
      ],
      "created": "2023-04-29 08:13:34",
      "modified": "2026-11-07 16:44:49",
      "commits": 14
    },
    {
      "source": "lca_exploratory.Rmd",
      "filename": "lca_exploratory.html",
      "title": "Exploratory LPA for Ocean Microplastics",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Loading the Data",
        "Descriptive statistics",
        "Conducting Latent Profile Analysis",
        "Class Enumeration",
        "Interpreting the Final Class Solution"
      ],
      "created": "2023-04-29 08:13:34",
      "modified": "2026-11-07 16:44:49",
      "commits": 11
    },
    {
      "source": "Generating_syntax.Rmd",
      "filename": "Generating_syntax.html",
      "title": "Generating syntax for structural equation models",
      "engine": "knitr::rmarkdown",
      "headings": [
        "The tidySEM workflow",
        "Example: Running a CFA",
        "Step 1: Check the variable names",
        "Guidelines for naming variables",
        "Step 2: Generate a dictionary",
        "Step 3: Generate syntax",
        "Step 4: Run the model",
        "Optional step 5: Access the dictionary, data, and syntax",
        "Optional step 6: Modify the dictionary and syntax",
        "Optional step 7: Adding paths"
      ],
      "created": "2019-12-26 07:49:48",
      "modified": "2025-03-02 12:58:15",
      "commits": 22
    },
    {
      "source": "lca_introduction.Rmd",
      "filename": "lca_introduction.html",
      "title": "Introduction to Latent Class Analysis",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Pre-Analysis",
        "Using Your Own Data",
        "Examining Observed Data",
        "Data Preprocessing",
        "Missing Data",
        "Model Specification",
        "Latent Profile Analysis (LPA) with Continuous Indicators",
        "Maximum Number of Classes",
        "Class Enumeration",
        "BIC",
        "BLRT",
        "Eliminating Models from Consideration",
        "Reporting Results",
        "Latent Class Analysis with Ordinal indicators",
        "Dichotomous indicators: mx_lca()",
        "Model Fitting",
        "Mixed indicator types: mx_mixed_lca()",
        "Classification Accuracy Deep Dive"
      ],
      "created": "2026-11-07 16:44:49",
      "modified": "2026-11-09 07:02:44",
      "commits": 2
    },
    {
      "source": "lca_ordinal.Rmd",
      "filename": "lca_ordinal.html",
      "title": "Latent Class Analysis for Ordinal Indicators",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Loading the Data",
        "Examining the Data",
        "Conducting Latent Class Analysis",
        "Class Enumeration",
        "Using BIC",
        "Theoretical considerations",
        "Interpreting the Final Class Solution",
        "Auxiliary Analyses"
      ],
      "created": "2023-01-05 17:21:08",
      "modified": "2026-11-09 07:02:44",
      "commits": 15
    },
    {
      "source": "lca_lcga.Rmd",
      "filename": "lca_lcga.html",
      "title": "Latent Class Growth Analysis",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Data preprocessing",
        "Model Estimation",
        "Class enumeration",
        "Scree plot",
        "Wald tests",
        "Trajectory plot"
      ],
      "created": "2023-04-29 08:13:34",
      "modified": "2026-11-07 16:44:49",
      "commits": 11
    },
    {
      "source": "mixed_lca.Rmd",
      "filename": "mixed_lca.html",
      "title": "Mixed Data LCA",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Requirements",
        "Example Data",
        "Model Estimation with mx_mixed_lca()",
        "Estimating a Single Class Solution",
        "Estimating Multiple Class Solutions",
        "Class Enumeration",
        "Examine Results",
        "Advanced Options",
        "Plotting the Model",
        "References"
      ],
      "created": "2025-12-29 19:45:45",
      "modified": "2026-04-12 15:58:33",
      "commits": 7
    },
    {
      "source": "openmx_ordinal.Rmd",
      "filename": "openmx_ordinal.html",
      "title": "Ordinal Indicators in OpenMx Models",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Simulate ordinal data",
        "Threshold syntax in as_ram()",
        "Fit the default threshold parameterization",
        "Testing the first threshold of X1",
        "Testing the second threshold of X3",
        "Using threshold_method = \"mx_deviances\"",
        "Why the two Wald tests should agree",
        "Reparametrizing the Model"
      ],
      "created": "2026-09-02 07:21:59",
      "modified": "2026-09-02 07:21:59",
      "commits": 1
    },
    {
      "source": "Plotting_graphs.Rmd",
      "filename": "Plotting_graphs.html",
      "title": "Plotting graphs for structural equation models",
      "engine": "knitr::rmarkdown",
      "headings": [
        "The tidySEM workflow",
        "Example: Graphing a CFA",
        "Step 1: Run an analysis",
        "Step 2: Plot the graph",
        "Optional step 3: Customizing the layout",
        "Automatically generate layout for a model",
        "Specifying layout manually in R",
        "Specifying layout in a spreadsheet program",
        "Examples of user-defined layout",
        "Step 4: Customize nodes and edges",
        "Customizing node and edge labels",
        "Customize labels of a sem_graph",
        "Optional step 5: accessing graph data before plotting",
        "Optional step 6: Access the nodes and edges",
        "Optional step 7: Modify the nodes and edges",
        "Plot the customized graph",
        "Connecting nodes",
        "Visual aspects",
        "Visual aspects of edges",
        "Visual aspects of nodes",
        "Visual aspects of edge labels",
        "Conditionally customize visual aspects",
        "Math Notation in Graphs"
      ],
      "created": "2019-12-15 09:12:08",
      "modified": "2026-09-04 05:35:12",
      "commits": 22
    },
    {
      "source": "sem_graph.Rmd",
      "filename": "sem_graph.html",
      "title": "SEM graphing conventions",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Nodes",
        "Observed variables",
        "Latent variables",
        "Edges",
        "Regression effects",
        "Covariances",
        "(Residual) variances",
        "Basic models",
        "Path models",
        "Measurement model",
        "Structural equation models"
      ],
      "created": "2020-06-01 14:48:52",
      "modified": "2021-11-16 14:41:10",
      "commits": 10
    },
    {
      "source": "SMART_LCA_checklist.Rmd",
      "filename": "SMART_LCA_checklist.html",
      "title": "SMART-LCA Checklist",
      "engine": "knitr::rmarkdown",
      "headings": [],
      "created": "2023-09-07 06:27:25",
      "modified": "2026-09-02 07:21:59",
      "commits": 4
    },
    {
      "source": "Tabulating_results.Rmd",
      "filename": "Tabulating_results.html",
      "title": "Tabulating results from structural equation models",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Output from lavaan",
        "Output from OpenMx",
        "Output from Mplus"
      ],
      "created": "2020-01-22 15:47:12",
      "modified": "2025-07-27 14:53:00",
      "commits": 16
    },
    {
      "source": "pmc_tutorial.Rmd",
      "filename": "pmc_tutorial.html",
      "title": "Tutorial PMC",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Example Data",
        "References"
      ],
      "created": "2026-04-12 15:58:33",
      "modified": "2026-11-07 16:44:49",
      "commits": 3
    }
  ],
  "_score": 11.52976932095656,
  "_indexed": true,
  "_nocasepkg": "tidysem",
  "_universes": [
    "cjvanlissa"
  ],
  "_binaries": [
    {
      "r": "4.7.0",
      "os": "linux",
      "version": "0.3.0",
      "date": "2026-11-09T08:05:42.000Z",
      "distro": "resolute",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/2c61c61aa38414600cfd99f3d08f11aee0bfa204f3fbc5c7e4ffb13778f6b677",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    },
    {
      "r": "4.6.2",
      "os": "linux",
      "version": "0.3.0",
      "date": "2026-11-09T08:05:51.000Z",
      "distro": "resolute",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/8bacb7e6547220112a0b6ec7da82580442ba89ea8b6124bd2e723de173183494",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    },
    {
      "r": "4.5.3",
      "os": "mac",
      "version": "0.3.0",
      "date": "2026-11-09T08:04:27.000Z",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/f01bc56dfeb390b276e164ba5606edd022f318b44ba98514120b836400b2f21b",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    },
    {
      "r": "4.6.2",
      "os": "mac",
      "version": "0.3.0",
      "date": "2026-11-09T08:04:23.000Z",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/00a0b525ae79ae555983e23dc50941cc86380b974b93cec6c882a7203efd6c25",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    },
    {
      "r": "4.6.0",
      "os": "wasm",
      "version": "0.3.0",
      "date": "2026-11-09T08:06:00.000Z",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/86601a66c6b57f6c033a4ea6511a2bbc246aac47ec7adb4b0f664263505674fb",
      "status": "success",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    },
    {
      "r": "4.7.0",
      "os": "win",
      "version": "0.3.0",
      "date": "2026-11-09T08:04:18.000Z",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/ac010b0caa6ebea6150248c5168428f470ec1f4791c493d2a0682038d17cdc73",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    },
    {
      "r": "4.5.3",
      "os": "win",
      "version": "0.3.0",
      "date": "2026-11-09T08:04:21.000Z",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/ef05c0beefda9a2f563c541dda60583eab9ec6b1fbf558be3329c642a0a684b3",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    },
    {
      "r": "4.6.2",
      "os": "win",
      "version": "0.3.0",
      "date": "2026-11-09T08:04:58.000Z",
      "commit": "b6eb160cad950964ccb82652bfc3a33217055923",
      "fileid": "https://r2.ropensci.org/b692d06d2c6a0cb092ad4d2b9def603ab9654470498432776e2bfaf11345554b",
      "status": "success",
      "check": "NOTE",
      "buildurl": "https://github.com/r-universe/cjvanlissa/actions/runs/42582358754"
    }
  ]
}