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 the already available R package 'sitar'. While the 'sitar' package allows modelling of a single outcome only, the 'bsitar' package offers great flexibility in fitting models of varying complexities, including joint modelling of multiple outcomes such as height and weight (multivariate model). Additionally, the 'bsitar' package allows for the simultaneous analysis of an outcome separately for subgroups defined by a factor variable such as gender. This is achieved by fitting separate models for each subgroup (for example males and females for gender variable). An advantage of this approach is that posterior draws for each subgroup are part of a single model object, making it possible to compare coefficients across subgroups and test hypotheses. Since the 'bsitar' package is a front-end to the R package 'brms', it offers excellent support for post-processing of posterior draws via various functions that are directly available from the 'brms' package. In addition, the 'bsitar' package includes various customized functions that allow for the visualization of distance (increase in size with age) and velocity (change in growth rate as a function of age), as well as the estimation of growth spurt parameters such as age at peak growth velocity and peak growth velocity.

Version:	0.3.2
Depends:	R (≥ 3.6)
Imports:	brms (≥ 2.22.0), rstan (≥ 2.32.6), loo (≥ 2.7.0), dplyr (≥ 1.1.3), rlang (≥ 1.1.2), Rdpack (≥ 2.6.2), insight (≥ 1.0.1), data.table (≥ 1.16.4), collapse (≥ 2.0.19), marginaleffects (≥ 0.25.0), sitar, magrittr, methods, utils
Suggests:	ggplot2 (≥ 3.4.0), bayesplot (≥ 1.11.0), posterior (≥ 1.3.1), testthat (≥ 3.0.0), dtplyr (≥ 1.3.1), checkmate (≥ 2.3.1), doParallel (≥ 1.0.17), parallel (≥ 4.3.1), foreach (≥ 1.5.2), ggridges (≥ 0.5.6), jtools (≥ 2.2.2), fastplyr (≥ 0.2.0), doFuture (≥ 1.0.1), cheapr (≥ 0.9.8), installr (≥ 0.23.4), splines2 (≥ 0.5.3), tidyr, nlme, purrr, future, future.apply, forcats, patchwork, tibble, pracma, extraDistr, bookdown, knitr, kableExtra, rmarkdown, spelling, Hmisc, R.rsp, graphics, grDevices, ggtext, glue, stats, here
Published:	2025-02-07
DOI:	10.32614/CRAN.package.bsitar
Author:	Satpal Sandhu [aut, cre, cph]
Maintainer:	Satpal Sandhu <satpal.sandhu at bristol.ac.uk>
BugReports:	https://github.com/Sandhu-SS/bsitar/issues
License:	GPL-2
URL:	https://github.com/Sandhu-SS/bsitar
NeedsCompilation:	no
Language:	en-US
Citation:	bsitar citation info
Materials:	README NEWS
CRAN checks:	bsitar results

Documentation:

Reference manual:	bsitar.pdf
Vignettes:	Bayesian SITAR model - An introduction (source, R code) Bayesian SITAR model fit (source, R code)

Downloads:

Package source:	bsitar_0.3.2.tar.gz
Windows binaries:	r-devel: bsitar_0.3.2.zip, r-release: bsitar_0.3.2.zip, r-oldrel: bsitar_0.3.2.zip
macOS binaries:	r-release (arm64): bsitar_0.3.2.tgz, r-oldrel (arm64): bsitar_0.2.1.tgz, r-release (x86_64): bsitar_0.3.2.tgz, r-oldrel (x86_64): bsitar_0.2.1.tgz
Old sources:	bsitar archive

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