cta: Contingency Table Analysis Based on ML Fitting of MPH Models

Contingency table analysis is performed based on maximum likelihood (ML) fitting of multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP) models. See Lang (2004) <doi:10.1214/aos/1079120140> and Lang (2005) <doi:10.1198/016214504000001042> for MPH and HLP models. Objects computed include model goodness-of-fit statistics; likelihood- based (cell- and link-specific) residuals; and cell probability and expected count estimates along with standard errors. This package can also compute test-inversion--e.g. Wald, profile likelihood, score, power-divergence--confidence intervals for contingency table estimands, when table probabilities are potentially subject to equality constraints. For test-inversion intervals, see Lang (2008) <doi:10.1002/sim.3391> and Zhu (2020) <doi:10.17077/etd.005331>.

Package details

AuthorJoseph B. Lang [aut], Qiansheng Zhu [aut, cre]
MaintainerQiansheng Zhu <qiansheng-zhu@uiowa.edu>
LicenseGPL (>= 2)
Version1.3.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("cta")

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cta documentation built on Aug. 24, 2021, 1:06 a.m.