Package: bsitar 0.2.2.02

bsitar: Bayesian Super Imposition by Translation and Rotation Growth Curve Analysis

The Super Imposition by Translation and Rotation (SITAR) model is a shape-invariant nonlinear mixed effect model that fits a natural cubic spline mean curve to the growth data, and aligns individual-specific growth curves to the underlying mean curve via a set of random effects (see Cole, 2010 <doi:10.1093/ije/dyq115> for details). The non-Bayesian version of the SITAR model can be fit by using an already available R package 'sitar'. While 'sitar' package allows modelling of a single outcome only, the 'bsitar' package offers a great flexibility in fitting models of varying complexities that include joint modelling of multiple outcomes such as height and weight (multivariate model). Also, the 'bsitar' package allows simultaneous analysis of an outcome separately for sub groups defined by a factor variable such as gender. This is achieved by fitting separate models for each sub group (such as males and females for gender variable). An advantage of such approach is that posterior draws for each sub group are part of a single model object that makes it possible to compare coefficients across groups and test hypotheses. As 'bsitar' package is a front-end to the R package 'brms', it offers an excellent support for post-processing of posterior draws via various functions that are directly available from the 'brms' package. In addition, the 'bsitar' package include various customized functions that allow estimation and visualization growth curves such as distance (increase in size with age) and velocity (change in growth rate as a function of age).

Authors:Satpal Sandhu [aut, cre, cph]

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bsitar/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/sandhu-ss/bsitar/issues

Datasets:
  • berkeley - Berkeley Child Guidance Study Data
  • berkeley_exdata - Berkeley Child Guidance Study Data for females
  • berkeley_exfit - Model fit to the Berkeley Child Guidance Study Data for females

On CRAN:

4.28 score 5 scripts 234 downloads 29 exports 89 dependencies

Last updated 3 hours agofrom:40affb30a9. Checks:ERROR: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesFAILNov 23 2024
R-4.5-winWARNINGNov 23 2024
R-4.5-linuxWARNINGNov 23 2024
R-4.4-winWARNINGNov 23 2024
R-4.4-macWARNINGNov 23 2024
R-4.3-winWARNINGNov 23 2024
R-4.3-macWARNINGNov 23 2024

Exports:%>%add_model_criterionbsitarexpose_model_functionsexpose_model_functions.bgmfitfitted_drawsfitted_draws.bgmfitgetNsObjectgrowthparametersgrowthparameters_comparisongrowthparameters_comparison.bgmfitgrowthparameters.bgmfitloo_validationloo_validation.bgmfitmarginal_comparisonmarginal_comparison.bgmfitmarginal_drawsmarginal_draws.bgmfitoptimize_modeloptimize_model.bgmfitplot_conditional_effectsplot_conditional_effects.bgmfitplot_curvesplot_curves.bgmfitplot_ppcpredict_drawspredict_draws.bgmfitupdate_modelupdate_model.bgmfit

Dependencies:abindbackportsbayesplotBHbridgesamplingbrmsBrobdingnagcallrcheckmateclicodacodetoolscollapsecolorspacecpp11data.tabledescdigestdistributionaldplyrfansifarverforcatsfurrrfuturefuture.applygenericsggplot2ggridgesglobalsgluegridExtragtableinlineinsightisobandlabelinglatticelifecyclelistenvloomagrittrmarginaleffectsMASSMatrixmatrixStatsmgcvmunsellmvtnormnleqslvnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6rbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackreshape2rlangrsamplerstanrstantoolsscalessitarsliderStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewarpwithr

Readme and manuals

Help Manual

Help pageTopics
Add model fit criteria to modeladd_model_criterion add_model_criterion.bgmfit
Berkeley Child Guidance Study Databerkeley
Berkeley Child Guidance Study Data for femalesberkeley_exdata
Model fit to the Berkeley Child Guidance Study Data for femalesberkeley_exfit
Fit Bayesian SITAR growth curve modelbsitar
Expose user defined Stan function for post-processingexpose_model_functions expose_model_functions.bgmfit
Fitted (expected) values from the posterior drawsfitted_draws fitted_draws.bgmfit
Check and get namespace object if existsgetNsObject
Estimate and compare growth parametersgrowthparameters_comparison growthparameters_comparison.bgmfit
Estimate growth parameters from the model fitgrowthparameters growthparameters.bgmfit
Perform leave-one-out (loo) cross-validationloo_validation loo_validation.bgmfit
Estimate and compare growth curvesmarginal_comparison marginal_comparison.bgmfit
Estimate growth curvesmarginal_draws marginal_draws.bgmfit
Optimize SITAR modeloptimize_model optimize_model.bgmfit
Visualize conditional effects of predictorplot_conditional_effects plot_conditional_effects.bgmfit
Plot growth curvesplot_curves plot_curves.bgmfit
Perform posterior predictive distribution checksplot_ppc plot_ppc.bgmfit
Predicted values from the posterior predictive distributionpredict_draws predict_draws.bgmfit
Update modelupdate_model update_model.bgmfit