cmm-package {cmm}R Documentation

Categorical Marginal Models


Quite extensive package for maximum likelihood estimation and weighted least squares estimation of categorical marginal models (CMMs; e.g., Bergsma & Rudas, 2002; Bergsma, Croon and Hagenaars, 2009


Package: cmm
Type: Package
Version: 1.0
Date: 2023-08-08
License: GPL (>= 2)

The package contains principal functions for analyzing marginal models for categorical data. All functions are illustrated using examples from the book Marginal Models for Dependent, Clustered, and Longitudunal Categorical Data (Bergsma, Croon, & Hagenaars, 2009).

The package contains the following functions ConstraintMatrix DesignMatrix DirectSum JoinModels MarginalMatrix MarginalModelFit ModelStatistics SampleStatistics SpecifyCoefficient

The package contains the following data sets Antisemitism BodySatisfaction ClarenceThomas DutchConcern DutchPolitics ErieCounty EVS GSS93 LaborParticipation MarihuanaAlcohol NES NKPS NKPS2 Smoking

As of version 1.0, the option of maximum augmented empirical likelihood estimation (MAEL) estimation (Van der Ark et al., 2023), which is particularly useful for large data set. The following functions were added: Margins RecordsToFrequencies; the following data set was added acl; and the following function was updated: MarginalMatrix.


Wicher P. Bergsma Maintainer: L. Andries van der Ark


Bergsma, W. P. (1997). Marginal models for categorical data. Tilburg, The Netherlands: Tilburg University Press.

Bergsma, W. P., Croon, M. A., & Hagenaars, J. A. P. (2009). Marginal models for dependent, clustered, and longitudunal categorical data. Berlin: Springer. doi:10.1007/b12532

Bergsma, W. P.& Rudas T. (2002). Marginal models for categorical data. The Annals of Statistics, 30, 1, 140-159. doi:10.1214/aos/1015362188

Van der Ark, L. A., Bergsma, W. P., & Koopman L. (2023) Maximum augmented empirical likelihood estimation of categorical marginal models for large sparse contingency tables. Paper submitted for publication.

[Package cmm version 1.0 Index]