MBRM: Mixed Regression Models with Generalized Log-Gamma Random
Effects
Multivariate distribution derived from a Bernoulli mixed model under a marginal approach, incorporating a non-normal random intercept whose distribution is assumed to follow a generalized log-gamma (GLG) specification under a particular parameter setting. Estimation is performed by maximizing the log-likelihood using numerical optimization techniques (Lizandra C. Fabio, Vanessa Barros, Cristian Lobos, Jalmar M. F. Carrasco, Marginal multivariate approach: A novel strategy for handling correlated binary outcomes, 2025, under submission).
| Version: |
0.1.1 |
| Depends: |
R (≥ 3.5) |
| Imports: |
Rcpp, stats, Formula, tibble, dplyr, ggplot2 |
| LinkingTo: |
Rcpp |
| Published: |
2025-12-22 |
| DOI: |
10.32614/CRAN.package.MBRM (may not be active yet) |
| Author: |
Lizandra C. Fabio [aut],
Vanessa Barros [aut],
Cristian Lobos [aut],
Jalmar M. F. Carrasco [aut, cre] |
| Maintainer: |
Jalmar M. F. Carrasco <carrasco.jalmar at ufba.br> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| CRAN checks: |
MBRM results |
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