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 a single 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).

Version: 0.2.1
Depends: R (≥ 3.6)
Imports: brms (≥ 2.17.0), rstan (≥ 2.26.0), loo (≥ 2.7.0), dplyr (≥ 1.1.3), rlang (≥ 1.1.2), Rdpack (≥ 2.5), insight (≥ 0.19.7), marginaleffects (≥ 0.18.0), sitar, magrittr, methods, utils
Suggests: ggplot2 (≥ 3.4.0), bayesplot (≥ 1.11.0), posterior (≥ 1.3.1), testthat (≥ 3.0.0), collapse (≥ 2.0.3), tidyr, nlme, purrr, future, future.apply, forcats, jtools, patchwork, tibble, pracma, extraDistr, bookdown, knitr, kableExtra, rmarkdown, spelling, Hmisc, R.rsp, graphics, grDevices, ggtext, glue, stats
Published: 2024-03-19
Author: Satpal Sandhu ORCID iD [aut, cre, cph]
Maintainer: Satpal Sandhu <satpal.sandhu at>
License: GPL-2
NeedsCompilation: no
Language: en-US
Citation: bsitar citation info
Materials: README NEWS
CRAN checks: bsitar results


Reference manual: bsitar.pdf
Vignettes: Bayesian SITAR model - An introduction


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


Please use the canonical form to link to this page.