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BEND  

Bayesian Estimation of Nonlinear Data (BEND)
View on CRAN: Click here


Download and install BEND package within the R console
Install from CRAN:
install.packages("BEND")

Install from Github:
library("remotes")
install_github("cran/BEND")

Install by package version:
library("remotes")
install_version("BEND", "1.0")



Attach the package and use:
library("BEND")
Maintained by
Corissa T. Rohloff
[Scholar Profile | Author Map]
First Published: 2024-03-23
Latest Update: 2024-03-23
Description:
Provides a set of models to estimate nonlinear longitudinal data using Bayesian estimation methods. These models include the: 1) Bayesian Piecewise Random Effects Model (Bayes_PREM()) which estimates a piecewise random effects (mixture) model for a given number of latent classes and a latent number of possible changepoints in each class, and can incorporate class and outcome predictive covariates (see Lamm (2022) and Lock et al., (2018) ), 2) Bayesian Crossed Random Effects Model (Bayes_CREM()) which estimates a linear, quadratic, exponential, or piecewise crossed random effects models where individuals are changing groups over time (e.g., students and schools; see Rohloff et al., (2024) ), and 3) Bayesian Bivariate Piecewise Random Effects Model (Bayes_BPREM()) which estimates a bivariate piecewise random effects model to jointly model two related outcomes (e.g., reading and math achievement; see Peralta et al., (2022) ).
How to cite:
Corissa T. Rohloff (2024). BEND: Bayesian Estimation of Nonlinear Data (BEND). R package version 1.0, https://cran.r-project.org/web/packages/BEND. Accessed 17 Feb. 2025.
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