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Description

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).

An overview

The bsitar package provides an interface for Bayesian implementation of Super Imposition by Translation and Rotation (SITAR) growth model. The SITAR is a shape-invariant nonlinear mixed effect model that fits a natural cubic spline mean curve and aligns individual-specific growth curves to the underlying mean curve via a set of random effects: the size, timing and intensity. The bsitar package package is a front-end to the R package brms which uses the Stan program to performing full Bayesian inference for a range of regression specifications including hierarchical multivariate modeling.

Installation

To install the latest release version from CRAN use

install.packages("bsitar")

The current developmental version can be downloaded from GitHub via

if (!requireNamespace("remotes")) {
  install.packages("remotes")
}
remotes::install_github("Sandhu-SS/bsitar")

The bsitar internally depends on the brms package which can be installed from the CRAN as

install.packages("brms")

The latest developmental version of brms can be downloaded from GitHub as

remotes::install_github("paul-buerkner/brms")

Note that the brms, and hence the bsitar too, are based on Stan, therefore
a C++ compiler is required. The program Rtools (available on https://cran.r-project.org/bin/windows/Rtools/) comes with a C++ compiler for Windows. On Mac, you should install Xcode. For further instructions on how to get the compilers running, see the prerequisites section on https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started.

Metadata

Version

0.2.1

License

Unknown

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