| SimCorMultRes-package {SimCorMultRes} | R Documentation |
Simulating Correlated Multinomial Responses
Description
Functions to simulate correlated multinomial responses (three or more nominal or ordinal response categories) and correlated binary responses subject to a marginal model specification.
Details
The simulated correlated binary or multinomial responses are drawn as realizations of a latent regression model for continuous random vectors with the correlation structure expressed in terms of the latent correlation.
For an ordinal response scale, the multinomial variables are simulated
conditional on a marginal cumulative link model
(rmult.clm), a marginal continuation-ratio model
(rmult.crm) or a marginal adjacent-category logit model
(rmult.acl).
For a nominal response scale, the multinomial responses are simulated
conditional on a marginal baseline-category logit model
(rmult.bcl).
Correlated binary responses are simulated using the function
rbin.
The threshold approaches that give rise to the implemented marginal models are fully described in Touloumis (2016) and in the Vignette.
The formulae are easier to read from either the Vignette or the Reference Manual (both available here).
Author(s)
Anestis Touloumis
Maintainer: Anestis Touloumis A.Touloumis@brighton.ac.uk
References
Cario, M. C. and Nelson, B. L. (1997) Modeling and generating random vectors with arbitrary marginal distributions and correlation matrix. Technical Report, Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois.
Emrich, L. J. and Piedmonte, M. R. (1991) A method for generating high-dimensional multivariate binary variates. The American Statistician 45, 302–304.
Li, S. T. and Hammond, J. L. (1975) Generation of pseudorandom numbers with specified univariate distributions and correlation coefficients. IEEE Transactions on Systems, Man and Cybernetics 5, 557–561.
McCullagh, P. (1980) Regression models for ordinal data. Journal of the Royal Statistical Society B 42, 109–142.
McFadden, D. (1974) Conditional logit analysis of qualitative choice behavior. New York: Academic Press, 105–142.
Touloumis, A. (2016) Simulating Correlated Binary and Multinomial Responses under Marginal Model Specification: The SimCorMultRes Package. The R Journal 8, 79–91.
Touloumis, A., Agresti, A. and Kateri, M. (2013) GEE for multinomial responses using a local odds ratios parameterization. Biometrics 69, 633–640.
Tutz, G. (1991) Sequential models in categorical regression. Computational Statistics & Data Analysis 11, 275–295.