Mean and Scale-Factor Modeling of Under- And Over-Dispersed Binary Data R package BinaryEPPM version 3.0 Under- and over-dispersed binary data are modeled using an extended Poisson process model (EPPM) appropriate for binary data. A feature of the model is that the under-dispersion relative to the binomial distribution only needs to be greater than zero, but the over-dispersion is restricted compared to other distributional models such as the beta and correlated binomials. Because of this, the examples focus on under-dispersed data and how, in combination with the beta or correlated distributions, flexible models can be fitted to data displaying both under- and over-dispersion. Using Generalized Linear Model (GLM) terminology, the functions utilize linear predictors for the probability of success and scale-factor with various link functions for p, and log link for scale-factor, to fit a variety of models relevant to areas such as bioassay. Details of the EPPM are in Faddy and Smith (2012) <doi:10.1002/bimj.201100214> and Smith and Faddy (2019) <doi:10.18637/jss.v090.i08>. Software Depends: R (>= 3.5.0) Imports: Formula, expm, numDeriv, stats, lmtest, grDevices, graphics Suggests: R.rsp David M. Smith <dmccsmith@verizon.net> Comprehensive R Archive Network (CRAN) David M. Smith [aut, cre], Malcolm J. Faddy [aut] GPL-2 2024-06-04 application/tgz https://CRAN.R-project.org/package=BinaryEPPM doi:10.32614/CRAN.package.BinaryEPPM