An extended class of marginal link functions for modelling contingency tables by equality and inequality constraints

90 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A Multivariate Extension of the Dynamic Logit Model for Longitudinal Data Based on a Latent Markov Heterogeneity Structure (2009, methodology): “To parameterize the conditional distribution of the vector of response variables, given the covariates, the lagged response variables, and the subject-specific parameters, we rely on a family of multivariate link functions formulated as in Colombi and Forcina (2001); this family has a structure simi”
Chain graph models of multivariate regression type for categorical data (2009, background): “The maximization of this likelihood under the above linear constraints has been discussed by several authors; see [2,3,13, 15], among others.”
Foundations of Linear and Generalized Linear Models (2015, background): “11 Marginal models, copulas, and composite likelihood: For ML for marginal and related models for contingency tables, see Bartolucci et al. (2007), Bergsma et al. (2009), and Lang (2004, 2005).”