ememax: Estimation for Binary Emax Models with Missing Responses and
Bias Reduction
Provides estimation utilities for binary Emax dose-response models. Includes Expectation-Maximization based maximum likelihood estimation when the binary response is missing, as well as bias-reduced estimators including Jeffreys-penalized likelihood, Firth-score, and Cox-Snell corrections.The methodology is described in Zhang, Pradhan, and Zhao (2025) <doi:10.1177/09622802251403356> and Zhang, Pradhan, and Zhao (2026) <doi:10.1080/10543406.2026.2627387>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.0.0), clinDR (≥ 2.5.2) |
| Imports: |
BB, brglm, boot, formula.tools, MASS, maxLik, numDeriv, stats |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-03-17 |
| DOI: |
10.32614/CRAN.package.ememax (may not be active yet) |
| Author: |
Jiangshan Zhang [aut, cre],
Vivek Pradhan [aut],
Yuxi Zhao [aut] |
| Maintainer: |
Jiangshan Zhang <jiszhang at ucdavis.edu> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
ememax results |
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