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bsitar
View on CRAN: Click
here
Download and install bsitar package within the R console
Install from CRAN:
install.packages("bsitar")
Install from Github:
library("remotes")
install_github("cran/bsitar")
Install by package version:
library("remotes")
install_version("bsitar", "0.3.2")
Attach the package and use:
library("bsitar")
Maintained by
Satpal Sandhu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.bsitar . https://github.com/Sandhu-SS/bsitar/issues . https://github.com/Sandhu-SS/bsitar . bsitar citation info . bsitar results . bsitar.pdf . bsitar_0.3.2.tar.gz . bsitar_0.3.2.zip . bsitar_0.3.2.zip . bsitar_0.3.2.zip . bsitar_0.3.2.tgz . bsitar_0.3.2.tgz . bsitar_0.3.2.tgz . bsitar_0.3.2.tgz . bsitar archive . https://CRAN.R-project.org/package=bsitar .
First Published: 2023-12-15
Latest Update: 2024-01-25
Description:
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 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).
How to cite:
Satpal Sandhu (2023). bsitar: Bayesian Super Imposition by Translation and Rotation Growth Curve Analysis. R package version 0.3.2, https://cran.r-project.org/web/packages/bsitar. Accessed 29 Apr. 2025.
Previous versions and publish date:
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