Package: BEND 1.0

Corissa T. Rohloff

BEND: Bayesian Estimation of Nonlinear Data (BEND)

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) <https://hdl.handle.net/11299/252533> and Lock et al., (2018) <doi:10.1007/s11336-017-9594-5>), 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) <doi:10.1111/bmsp.12334>), 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) <doi:10.1037/met0000358>).

Authors:Corissa T. Rohloff [aut, cre], Rik Lamm [aut], Yadira Peralta [aut], Nidhi Kohli [aut], Eric F. Lock [aut]

BEND_1.0.tar.gz
BEND_1.0.tar.gz(r-4.5-noble)BEND_1.0.tar.gz(r-4.4-noble)
BEND_1.0.tgz(r-4.4-emscripten)BEND_1.0.tgz(r-4.3-emscripten)
BEND.pdf |BEND.html
BEND/json (API)
NEWS

# Install 'BEND' in R:
install.packages('BEND', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/crohlo/bend/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:

jagscpp

1.70 score 218 downloads 4 exports 6 dependencies

Last updated 9 months agofrom:13a5ec9842. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 01 2024
R-4.5-linuxOKDec 01 2024

Exports:Bayes_BPREMBayes_CREMBayes_PREMplot_BEND

Dependencies:codacombinatlabel.switchinglatticelpSolverjags