Description: Routines for fitting Logic Regression models. Logic Regression is described
in Ruczinski, Kooperberg, and LeBlanc (2003) <DOI:10.1198/1061860032238>. Monte
Carlo Logic Regression is described in and Kooperberg and Ruczinski (2005)

Title: Logistic Curve Fitting by Rhodes Method
Description: A system for fitting Logistic Curve by Rhodes Method. Method for fitting logistic curve by Rhodes Method is described in A.M.Gun,M.K.Gupta and B.Dasgupta(2019,ISBN:81-87567-81-3).

Title: Diagnostic tests for logistic regression models
Description: Diagnostic tests and plots for logistic regression models.
Depends: R (>= 2.13.0), multcomp, data.table, pROC, car
Imports: gRbase, rms, stats, statmod, graphics, speedglm
Collate: 'genLogi.R' 'logiDx.R' 'stukel.R' 'logiGOF.R' 'logiProb.R'

Title: Diagnostic Tests for Models with a Binomial Response
Description: Diagnostic tests and plots for GLMs (generalized linear models)
with binomial/ binary outcomes, particularly logistic regression.
Imports: rms, stats, statmod, graphics, speedglm, RColorBrewer,
Collate: 'LogisticDx_package.R' 'OR.R' 'ageChd.R' 'bbdm.R' 'dx.R'
'genBinom.R' 'gof.R' 'icu.R' 'lbw.R' 'llbw.R' 'mes.R' 'mlbw.R'
'nhanes3.R' 'pcs.R' 'plotGlm.R' 'printGofGlm.R' 'printSSglm.R'

Title: Diagnostic Tests for Logistic Regression Models

Title: Linear and Logistic Regression-Based Reliable Change Index
Authors@R: c(person("Rafael", "de Andrade Moral", role = c("aut", "cre"), email = "rafael.deandrademoral@mu.ie"), person("Unai", "Diaz-Orueta", role = "aut"), person("Javier", "Oltra-Cucarella", role = "aut"))
Imports: methods, graphics, stats, utils
Description: Here we provide an implementation of the linear and logistic regression-based Reliable Change Index (RCI), to be used with lm and binomial glm model objects, respectively, following Moral et al. <https://psyarxiv.com/gq7az/>. The RCI function returns a score assumed to be approximately normally distributed, which is helpful to detect patients that may present cognitive decline.

Title: Infer network based on binary arrays using regularized logistic
Author: Pei Wang <pwang@fhcrc.org>, Dennis Chao <dchao@fhcrc.org>, Li
Description: LogitNet is developed for inferring network of binary
variables under the high-dimension-low-sample-size setting