Contingency Table Analysis Based on ML Fitting of MPH Models
Description
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) and Lang (2005)
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) and Zhu (2020) .