Package: slca 1.2.0

slca: Structural Modeling for Multiple Latent Class Variables

Provides comprehensive tools for the implementation of Structural Latent Class Models (SLCM), including Latent Transition Analysis (LTA; Linda M. Collins and Stephanie T. Lanza, 2009) <doi:10.1002/9780470567333>, Latent Class Profile Analysis (LCPA; Hwan Chung et al., 2010) <doi:10.1111/j.1467-985x.2010.00674.x>, and Joint Latent Class Analysis (JLCA; Saebom Jeon et al., 2017) <doi:10.1080/10705511.2017.1340844>, and any other extended models involving multiple latent class variables.

Authors:Youngsun Kim [aut, cre], Hwan Chung [aut]

slca_1.2.0.tar.gz
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slca.pdf |slca.html
slca/json (API)

# Install 'slca' in R:
install.packages('slca', repos = c('https://kim0sun.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/kim0sun/slca/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • addhealth - Adolescent Depression Data from the Add Health Study
  • gss7677 - GSS 1976-1977 Data on Social Status and Tolerance towards Minorities
  • nlsy97 - NLSY97 Substance Use Data
  • nlsy_jlcpa - JLCPA Model Estimated with NLSY97 Data
  • nlsy_jlta - JLCPA Model Estimated with NLSY97 Data

On CRAN:

3.81 score 4 scripts 126 downloads 7 exports 68 dependencies

Last updated 6 days agofrom:f13586751d. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-win-x86_64OKOct 31 2024
R-4.5-linux-x86_64OKOct 31 2024
R-4.4-win-x86_64OKOct 31 2024
R-4.4-mac-x86_64OKOct 31 2024
R-4.4-mac-aarch64OKOct 31 2024
R-4.3-win-x86_64OKOct 31 2024
R-4.3-mac-x86_64OKOct 31 2024
R-4.3-mac-aarch64OKOct 31 2024

Exports:compareestimategofparamregressslcaslcaControl

Dependencies:base64encbitbit64bslibcachemclicliprcolorspacecpp11crayonDiagrammeRdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsgluehighrhmshtmltoolshtmlwidgetsigraphjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemimemunsellpillarpkgconfigprettyunitsprogresspurrrR6rappdirsRColorBrewerRcppreadrrlangrmarkdownrstudioapisassscalesstringistringrtibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml