testthat (>= 3.0.0), Rcpp, RcppArmadillo
ggplot2, knitr, rmarkdown, dplyr, testthat (>= 3.0.0), xml2

ggplot2, knitr, rmarkdown, dplyr, testthat (>= 3.0.1), xml2

Fits logistic regression models by maximum penalized likelihood

Logistic regression models by maximum penalized likelihood.  Now superseded by the brglm package.

Bias Reduction with Missing Binary Response
c(person("Arnab", "Maity", email = "akumar@stat.tamu.edu", role = c("aut", "cre")),
person("Vivek", "Pradhan", email = "vip296@mail.harvard.edu", role = "ctb"),
person("Ujjwal", "Das", email = "ujjwal.das@iimu.ac.in", role = "ctb"))
Provides two main functions, il() and fil(). The il() function implements the EM algorithm developed by Ibrahim and Lipsitz (1996) <DOI:10.2307/2533068> to estimate the parameters of a logistic regression model with the missing response when the missing data mechanism is nonignorable. The fil() function implements the algorithm proposed by Maity et. al. (2017+) <https://github.com/arnabkrmaity/brlrmr> to reduce the bias produced by the method of Ibrahim and Lipsitz (1996) <DOI:10.2307/2533068>.
boot, brglm, MASS, profileModel, Rcpp, stats
Arnab Maity [aut, cre],
Vivek Pradhan [ctb],
Ujjwal Das [ctb]

c(person("Arnab", "Maity", email = "arnab.maity@pfizer.com", role = c("aut", "cre")),
person("Vivek", "Pradhan", email = "vip296@mail.harvard.edu", role = "aut"),
person("Ujjwal", "Das", email = "ujjwal.das@iimu.ac.in", role = "aut"))
Arnab Maity [aut, cre],
Vivek Pradhan [aut],
Ujjwal Das [aut]

Fits novel models for the conditional relative risk, risk difference and odds ratio.

Linbo Wang, Mark Clements, Thomas Richardson
Fits novel models for the conditional relative risk, risk difference and odds ratio <doi:10.1080/01621459.2016.1192546>.

person("Paul-Christian", "Buerkner", email = "paul.buerkner@gmail.com",
role = c("aut", "cre"))
Write and fit Bayesian generalized linear mixed models using Stan for full Bayesian inference.

loo (>= 0.1.6), shinystan (>= 2.2.0), gridExtra (>= 2.0.0),
lme4 (>= 1.1-11), Matrix (>= 1.1.1), mgcv (>= 1.7-23), coda,
abind, statmod, stats, graphics, utils, parallel, grDevices,
grid
testthat (>= 0.9.1), arm, mvtnorm, KernSmooth, R.rsp, knitr,
rmarkdown
Fit Bayesian generalized (non-)linear mixed models using Stan for full
Bayesian inference.