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 |
Documentation:
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