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>.

Version: 1.3.0
Imports: intervals, numDeriv, limSolve, methods
Suggests: vcd, MASS
Published: 2021-08-23
Author: Joseph B. Lang [aut], Qiansheng Zhu [aut, cre]
Maintainer: Qiansheng Zhu <qiansheng-zhu at uiowa.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: cta results


Reference manual: cta.pdf


Package source: cta_1.3.0.tar.gz
Windows binaries: r-devel: cta_1.3.0.zip, r-release: cta_1.3.0.zip, r-oldrel: cta_1.3.0.zip
macOS binaries: r-release (arm64): cta_1.3.0.tgz, r-release (x86_64): cta_1.3.0.tgz, r-oldrel: cta_1.3.0.tgz


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