Inflated Ordered Probit and Logit Models R package iop version 0.1.0 Estimation, inference, and quantities of interest for ordered probit and ordered logit models whose outcome contains an inflated category: a single ordered category (bottom, middle, top, or any other) that mixes observations generated by the ordered process with observations generated by a distinct split-population process. Fits the zero-inflated ordered probit of Harris and Zhao (2007) <doi:10.1016/j.jeconom.2007.01.002> and its middle- and top-inflated extensions (Bagozzi and Mukherjee 2012 <doi:10.1093/pan/mps020>; Bagozzi, Hill, Moore and Mukherjee 2015 <doi:10.1177/0022002713520530>; Bagozzi, Joo and Mukherjee 2024 <doi:10.1093/fpa/orae006>), generalized to an arbitrary inflated category and to the logit link, with optional correlated errors for the probit form, plus the standard ordered probit and logit and their partial proportional-odds (non-parallel) variants on the same footing. Provides analytic, robust, and cluster-robust standard errors, survey weights and offsets, model comparison (Vuong, likelihood-ratio, information criteria), regime-specific predicted probabilities and first differences, simulation for residual diagnostics, and tidy/table-package integration. The likelihood, its gradient, and the bivariate-normal probabilities are implemented in C++. Software Depends: R (>= 4.0) Imports: Rcpp, stats, graphics, methods, numDeriv, MASS LinkingTo: Rcpp Suggests: ordinal, VGAM, mvtnorm, pbivnorm, sandwich, DHARMa, testthat (>= 3.0.0), knitr, rmarkdown, broom, modelsummary, texreg, parallel, AER Benjamin E. Bagozzi <bagozzib@udel.edu> Comprehensive R Archive Network (CRAN) Benjamin E. Bagozzi [aut, cre] GPL-3 2026-09-03 application/tgz https://CRAN.R-project.org/package=iop doi:10.32614/CRAN.package.iop