Package: lcsm 0.3.2

lcsm: Univariate and Bivariate Latent Change Score Modelling

Helper functions to implement univariate and bivariate latent change score models in R using the 'lavaan' package. For details about Latent Change Score Modeling (LCSM) see McArdle (2009) <doi:10.1146/annurev.psych.60.110707.163612> and Grimm, An, McArdle, Zonderman and Resnick (2012) <doi:10.1080/10705511.2012.659627>. The package automatically generates 'lavaan' syntax for different model specifications and varying timepoints. The 'lavaan' syntax generated by this package can be returned and further specifications can be added manually. Longitudinal plots as well as simplified path diagrams can be created to visualise data and model specifications. Estimated model parameters and fit statistics can be extracted as data frames. Data for different univariate and bivariate LCSM can be simulated by specifying estimates for model parameters to explore their effects. This package combines the strengths of other R packages like 'lavaan', 'broom', and 'semPlot' by generating 'lavaan' syntax that helps these packages work together.

Authors:Milan Wiedemann [aut, cre], Graham M Thew [ctb], Urška Košir [ctb], Anke Ehlers [ths], Mental Health Research UK [fnd]

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lcsm.pdf |lcsm.html✨
lcsm/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/milanwiedemann/lcsm/issues

Datasets:
  • data_bi_lcsm - Longitudinal dataset with repeated measures of two constructs
  • data_uni_lcsm - Longitudinal dataset with repeated measures of one constructs
  • lcsm_data - Longitudinal dataset with repeated measures of two constructs

On CRAN:

6.34 score 17 stars 43 scripts 360 downloads 14 exports 117 dependencies

Last updated 2 years agofrom:501d0d242f. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-winNOTENov 22 2024
R-4.5-linuxNOTENov 22 2024
R-4.4-winNOTENov 22 2024
R-4.4-macNOTENov 22 2024
R-4.3-winNOTENov 22 2024
R-4.3-macNOTENov 22 2024

Exports:%>%extract_fitextract_paramfit_bi_lcsmfit_uni_lcsmplot_lcsmplot_trajectoriesrename_lcsm_varsselect_bi_casesselect_uni_casessim_bi_lcsmsim_uni_lcsmspecify_bi_lcsmspecify_uni_lcsm

Dependencies:abindarmbackportsbase64encBHbootbroombslibcachemcarDatacheckmatecliclustercodacolorspacecorpcorcpp11data.tabledigestdplyrevaluatefansifarverfastmapfdrtoolfontawesomeforeignFormulafsgenericsggplot2glassoglueGPArotationgridExtragtablegtoolshighrHmischtmlTablehtmltoolshtmlwidgetsigraphisobandjpegjquerylibjsonliteknitrkutilslabelinglatticelavaanlifecyclelisrelToRlme4magrittrMASSMatrixmemoisemgcvmimimeminqamnormtmunsellmvtnormnlmenloptrnnetnumDerivOpenMxopenxlsxpbapplypbivnormpillarpkgconfigplyrpngpsychpurrrqgraphquadprogR6rappdirsRColorBrewerRcppRcppEigenRcppParallelreshape2rlangrmarkdownrockchalkrpartrpfrstudioapiRUnitsassscalessemsemPlotStanHeadersstringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunXMLxtableyamlzip

Create path diagrams to visualise model specifications

Rendered fromv2-path-diagrams.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2021-07-10
Started: 2020-05-25

Generate lavaan syntax for latent change score models

Rendered fromv1-lavaan-syntax.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2021-07-10
Started: 2020-05-25

LCSM Parameters

Rendered fromlcsm-parameters.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2021-07-14
Started: 2021-07-10

Parameter estimates and fit statistics of LCSMs

Rendered fromv3-extract-tutorial.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2021-07-10
Started: 2020-06-03

Simulate data to explore the effect of different parameters

Rendered fromv4-simulate-data.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2023-01-30
Started: 2020-05-25

Visualise longitudinal data

Rendered fromv0-longitudinal-plots.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2020-06-03
Started: 2020-05-25