{ "_id": "6ae6b6061e2c7b3a4f52f681", "Package": "tseLCA", "Type": "Package", "Title": "Three-Step Estimation for Latent Class Analysis", "Version": "2.1.1", "Authors@R": "c(\nperson(\"Sam\", \"Lee\", email = \"samlee@arizona.edu\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0009-0007-2977-6661\")),\nperson(\"Jay\", \"Goodliffe\", email = \"goodliffe@byu.edu\", role = c(\"aut\", \"cph\"),\ncomment = c(ORCID = \"0000-0001-8272-7235\")\n)\n)", "Description": "Bias-adjusted three-step estimation of latent class models\nwith covariates and distal outcomes. The latent class\nmeasurement model is estimated first, with 'multilevLCA'\n(Lyrvall et al., 2025) , and\nheld fixed; observations are then classified; and the classes\nare related to covariates and distal outcomes with the maximum\nlikelihood correction of Vermunt (2010)\n and Bakk, Tekle and Vermunt (2013)\n, or the correction of Bolck,\nCroon and Hagenaars (2004) . Standard\nerrors account for the uncertainty of the measurement model\n(Bakk, Oberski and Vermunt, 2014) .\nIncludes class enumeration, modal and proportional class\nassignment, covariate formulas, Gaussian, Poisson, binomial,\nand multinomial distal outcomes, the two-step estimator of Bakk\nand Kuha (2018) , measurement\nmodels applied to new samples, and full-information maximum\nlikelihood for missing indicators, standard methods for fitted\nmodels, and a data-generating process replicating the\nsimulation design of Bakk and Kuha (2018).", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Language": "en-US", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "URL": "https://samleebyu.github.io/tseLCA/,\nhttps://github.com/SamLeeBYU/tseLCA", "BugReports": "https://github.com/SamLeeBYU/tseLCA/issues", "VignetteBuilder": "knitr, rmarkdown", "NeedsCompilation": "no", "Packaged": { "Date": "2026-11-01 03:42:34 UTC", "User": "root" }, "Author": "Sam Lee [aut, cre, cph] (ORCID:\n), Jay Goodliffe [aut,\ncph] (ORCID: )", "Maintainer": "Sam Lee ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-31 21:30:02 UTC", "RemoteUrl": "https://github.com/cran/tseLCA", "RemoteRef": "HEAD", "RemoteSha": "7c6c0f83b69018b00eb589ca54bf1695efa4ccb3", "_user": "cran", "_type": "src", "_file": "tseLCA_2.1.1.tar.gz", "_fileid": "https://r2.ropensci.org/07edb49ab6b931ac2b70bf9b0718d33fe8ce83e86cb53497238c74c0ad9ec058", "_filesize": 672463, "_sha256": "07edb49ab6b931ac2b70bf9b0718d33fe8ce83e86cb53497238c74c0ad9ec058", "_expires": "2027-02-09T03:46:12.000Z", "_created": "2026-11-01T03:42:34.000Z", "_published": "2026-11-01T03:46:14.709Z", "_upstream": "https://github.com/cran/tseLCA", "_status": "success", "_maintainer": { "name": "Sam Lee", "email": "samlee@arizona.edu", "orcid": "0009-0007-2977-6661" }, "_jobs": [ { "job": 124741452160, "time": 169, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13069375465" }, { "job": 124741452159, "time": 174, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "13068877920" }, { "job": 124740725513, "time": 233, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "13068124793" }, { "job": 124741452030, "time": 121, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "13069465234" }, { "job": 124741452077, "time": 118, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13068593991" }, { "job": 124741452064, "time": 144, "config": "windows-release-x86_64", "r": "4.6.2", "check": "OK", "artifact": "13069420334" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/41270005596", "_commit": { "id": "7c6c0f83b69018b00eb589ca54bf1695efa4ccb3", "author": "Sam Lee ", "committer": "cran-robot ", "message": "version 2.1.1\n", "time": 1793482202 }, "_distro": "resolute", "_host": "GitHub-Actions", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "cli", "role": "Imports" }, { "package": "Formula", "role": "Imports" }, { "package": "multilevLCA", "role": "Imports" }, { "package": "nnet", "role": "Suggests" }, { "package": "poLCA", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "parallel", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "spelling", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2026-28", "n": 1 }, { "week": "2026-38", "n": 1 }, { "week": "2026-39", "n": 1 }, { "week": "2026-40", "n": 1 }, { "week": "2026-43", "n": 1 }, { "week": "2026-44", "n": 1 } ], "_tags": [ { "name": "1.0.2", "date": "2026-07-11" }, { "name": "1.1.0", "date": "2026-09-20" }, { "name": "1.1.1", "date": "2026-09-23" }, { "name": "2.0.0", "date": "2026-10-01" }, { "name": "2.1.0", "date": "2026-10-24" }, { "name": "2.1.1", "date": "2026-10-31" } ], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "followers": 635, "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 500, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/tseLCA" }, "_devurl": "https://github.com/samleebyu/tselca", "_pkgdown": "https://samleebyu.github.io/tseLCA/", "_searchresults": 0, "_rbuild": "4.6.1", "_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/tseLCA.html" ], "_homeurl": "https://github.com/samleebyu/tselca", "_realowner": "samleebyu", "_cranurl": false, "_releases": [ { "version": "1.0.2", "date": "2026-07-11" }, { "version": "1.1.0", "date": "2026-09-20" }, { "version": "1.1.1", "date": "2026-09-23" }, { "version": "2.0.0", "date": "2026-10-01" }, { "version": "2.1.0", "date": "2026-10-24" }, { "version": "2.1.1", "date": "2026-10-31" } ], "_exports": [ "as_tse_lca", "best_model", "bk2018_params", "class_sizes", "classes", "classification", "covariate", "distal", "draw_classes", "draw_classes_given_Zp", "draw_indicators", "draw_Zo", "draw_Zp", "fitZ_from_fit0", "fitZ_from_multiLCA", "generate_all_conditions", "generate_data", "item_probs", "lca_step1", "lca_step1_startval", "make_rho", "measurement", "mnl_probs", "omnibus_test", "posterior", "three_step", "tse_classify", "tse_control", "tse_covariate", "tse_distal", "tse_lca", "tse_twostep", "tseLCA" ], "_help": [ { "page": "anova.tseLCA_covariate", "title": "Wald tests of covariate terms", "topics": [ "anova.tseLCA_covariate" ] }, { "page": "as_tse_lca", "title": "Use a measurement model with given parameters (Step 1)", "topics": [ "as_tse_lca" ] }, { "page": "best_model", "title": "Class enumeration results", "topics": [ "as.data.frame.tseLCA_select", "best_model", "best_model.tseLCA_select", "plot.tseLCA_select", "print.tseLCA_select", "[[.tseLCA_select" ] }, { "page": "bk2018_params", "title": "Default population parameters for the Bakk & Kuha (2018) simulation", "topics": [ "bk2018_params" ] }, { "page": "class_sizes", "title": "Class sizes and item-response probabilities of the measurement model", "topics": [ "class_sizes", "class_sizes.tseLCA", "item_probs", "item_probs.tseLCA" ] }, { "page": "coef.tseLCA_structural", "title": "Coefficients of a fitted tseLCA model", "topics": [ "coef.tseLCA_measurement", "coef.tseLCA_structural" ] }, { "page": "draw_classes", "title": "Draw latent class memberships from their marginal distribution", "topics": [ "draw_classes" ] }, { "page": "draw_classes_given_Zp", "title": "Draw latent classes conditional on the covariate (scenario \"covariate\")", "topics": [ "draw_classes_given_Zp" ] }, { "page": "draw_indicators", "title": "Draw binary indicators given true class memberships", "topics": [ "draw_indicators" ] }, { "page": "draw_Zo", "title": "Draw a continuous distal outcome given true class memberships (scenario \"distal\")", "topics": [ "draw_Zo" ] }, { "page": "draw_Zp", "title": "Draw the covariate Zp ~ Uniform{1, 2, 3, 4, 5}", "topics": [ "draw_Zp" ] }, { "page": "fitZ_from_fit0", "title": "Estimate covariate effects with measurement parameters fixed (two-step EM)", "topics": [ "fitZ_from_fit0" ] }, { "page": "fitZ_from_multiLCA", "title": "Estimate two-step covariate model with multilevLCA (optional reference path)", "topics": [ "fitZ_from_multiLCA" ] }, { "page": "generate_all_conditions", "title": "Generate datasets for all 18 conditions in the simulation design", "topics": [ "generate_all_conditions" ] }, { "page": "generate_data", "title": "Generate one dataset following the Bakk & Kuha (2018) simulation design", "topics": [ "generate_data" ] }, { "page": "lca_step1", "title": "Fit the LCA measurement model (Step 1)", "topics": [ "lca_step1" ] }, { "page": "logLik.tseLCA", "title": "Log-likelihood, number of observations, and information criteria", "topics": [ "logLik.tseLCA", "nobs.tseLCA" ] }, { "page": "make_rho", "title": "Build the item-response probability matrix for the simulation", "topics": [ "make_rho" ] }, { "page": "measurement", "title": "Components of a fitted tseLCA model", "topics": [ "classification", "classification.tseLCA", "covariate", "covariate.tseLCA", "distal", "distal.tseLCA", "measurement", "measurement.tseLCA" ] }, { "page": "mnl_probs", "title": "Compute multinomial logistic class probabilities given covariates", "topics": [ "mnl_probs" ] }, { "page": "omnibus_test", "title": "Omnibus Wald test of class equality for a distal outcome", "topics": [ "omnibus_test", "omnibus_test.tseLCA_both", "omnibus_test.tseLCA_distal" ] }, { "page": "plot.tseLCA", "title": "Plot item-response probability profiles for a tseLCA model", "topics": [ "plot.tseLCA" ] }, { "page": "posterior", "title": "Posterior class-membership probabilities and modal class assignments", "topics": [ "classes", "classes.tseLCA", "posterior", "posterior.tseLCA" ] }, { "page": "predict.tseLCA_covariate", "title": "Class-membership probabilities from a covariate model", "topics": [ "predict.tseLCA_covariate" ] }, { "page": "predict.tseLCA_measurement", "title": "Class membership predictions from a measurement model", "topics": [ "fitted.tseLCA_measurement", "predict.tseLCA_measurement" ] }, { "page": "relevel.tseLCA_covariate", "title": "Change the reference class of a covariate model", "topics": [ "relevel.tseLCA_covariate" ] }, { "page": "summary.tseLCA_structural", "title": "Summarize a fitted tseLCA model", "topics": [ "coef.summary.tseLCA_structural", "print.summary.tseLCA_measurement", "print.summary.tseLCA_structural", "print.tseLCA_measurement", "print.tseLCA_structural", "summary.tseLCA_measurement", "summary.tseLCA_structural" ] }, { "page": "three_step", "title": "Three-step LCA estimation with covariates and/or distal outcomes", "topics": [ "three_step" ] }, { "page": "tse_classify", "title": "Assign observations to latent classes (Step 2)", "topics": [ "print.tseLCA_classify", "tse_classify" ] }, { "page": "tse_control", "title": "Estimation settings for tseLCA models", "topics": [ "tse_control" ] }, { "page": "tse_covariate", "title": "Relate latent classes to covariates (Step 3)", "topics": [ "tse_covariate" ] }, { "page": "tse_distal", "title": "Relate latent classes to a distal outcome (Step 3)", "topics": [ "tse_distal" ] }, { "page": "tse_lca", "title": "Fit a latent class measurement model (Step 1)", "topics": [ "tse_lca" ] }, { "page": "tse_twostep", "title": "Two-step estimates of covariate effects", "topics": [ "tse_twostep" ] }, { "page": "tseLCA", "title": "Three-step latent class analysis in one call", "topics": [ "tseLCA" ] }, { "page": "vcov.tseLCA_structural", "title": "Variance-covariance matrix of a fitted tseLCA model", "topics": [ "vcov.tseLCA_measurement", "vcov.tseLCA_structural" ] } ], "_readme": "https://github.com/cran/tseLCA/raw/HEAD/README.md", "_rundeps": [ "base64enc", "bit", "bit64", "bslib", "cachem", "class", "classInt", "cli", "clipr", "cluster", "clustMixType", "codetools", "combinat", "commonmark", "cpp11", "crayon", "digest", "dplyr", "e1071", "fastmap", "fontawesome", "forcats", "foreach", "Formula", "fs", "generics", "glue", "haven", "highr", "hms", "htmltools", "httpuv", "iterators", "jquerylib", "jsonlite", "KernSmooth", "klaR", "labelled", "later", "lifecycle", "magrittr", "MASS", "mclust", "memoise", "mime", "miniUI", "multilevLCA", "otel", "pillar", "pkgconfig", "pracma", "prettyunits", "progress", "promises", "proxy", "purrr", "questionr", "R.cache", "R.methodsS3", "R.oo", "R.utils", "R6", "rappdirs", "RColorBrewer", "Rcpp", "RcppArmadillo", "readr", "rlang", "rprojroot", "rstudioapi", "sass", "shiny", "sourcetools", "stringi", "stringr", "styler", "tibble", "tictoc", "tidyr", "tidyselect", "tzdb", "utf8", "vctrs", "vroom", "withr", "xfun", "xtable" ], "_vignettes": [ { "source": "tseLCA-workflow.Rmd", "filename": "tseLCA-workflow.html", "title": "tseLCA Workflow", "engine": "knitr::rmarkdown", "headings": [ "Overview", "Example data", "Step 1: the measurement model", "Choosing the number of classes", "Inspecting the measurement model", "Step 2: classification", "Step 3: covariates", "Estimators and standard errors", "Reference class and covariate formulas", "Step 3: distal outcomes", "Covariates and a distal outcome", "All steps in one call", "A measurement model from another sample", "Missing data and indicator coding", "Estimation settings", "Migrating from tseLCA 1.x", "References" ], "created": "2026-07-11 08:40:02", "modified": "2026-10-31 21:30:02", "commits": 5 } ], "_score": 3.4771212547196626, "_indexed": false, "_nocasepkg": "tselca", "_universes": [ "cran" ], "_indexurl": "https://samleebyu.r-universe.dev/tseLCA", "_previous": "2.1.0", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.1.1", "date": "2026-11-01T03:45:01.000Z", "distro": "resolute", "commit": "7c6c0f83b69018b00eb589ca54bf1695efa4ccb3", "fileid": "https://r2.ropensci.org/40ec0e6bd4a4149dc7da2c88a3c94991b6fa5bac0bda46203b3cac646dfe0c68", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41270005596" }, { "r": "4.6.1", "os": "linux", "version": "2.1.1", "date": "2026-11-01T03:44:56.000Z", "distro": "resolute", "commit": "7c6c0f83b69018b00eb589ca54bf1695efa4ccb3", "fileid": "https://r2.ropensci.org/a4dc6b31e35aa073e1258b460435e609b87451fa1be95a5a9fb92876028cf485", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41270005596" }, { "r": "4.6.0", "os": "wasm", "version": "2.1.1", "date": "2026-11-01T03:45:03.000Z", "commit": "7c6c0f83b69018b00eb589ca54bf1695efa4ccb3", "fileid": "https://r2.ropensci.org/86448afe8fe6cec5392d7051b468fde14ad1ef0e54f53f12e9474b0df99429a1", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/41270005596" }, { "r": "4.7.0", "os": "win", "version": "2.1.1", "date": "2026-11-01T03:43:56.000Z", "commit": "7c6c0f83b69018b00eb589ca54bf1695efa4ccb3", "fileid": "https://r2.ropensci.org/d210d39cd5248e5cf1c40e4af3370e69f0f2bc1db8910d66448972c7fe94547b", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41270005596" }, { "r": "4.6.2", "os": "win", "version": "2.1.1", "date": "2026-11-01T03:44:03.000Z", "commit": "7c6c0f83b69018b00eb589ca54bf1695efa4ccb3", "fileid": "https://r2.ropensci.org/765273811d2ad3430dc86c706cdf8bbbd111a817c710126e287e75e4a6cdd89a", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41270005596" } ] }