Generating Random Binary Deviates Having Fixed Marginal Distributions and Specified Degrees of Association

1 August 1993

journal article
research article
Published by Taylor & Francis in The American Statistician

Vol. 47 (3) , 209-215
https://doi.org/10.1080/00031305.1993.10475980

Abstract

Models for the analysis of correlated binary data have attracted considerable interest in the last few years. Parameter estimation in such models is based on asymptotic theory, and the small-sample properties of estimators must be studied by simulation. In this article we discuss several flexible methods for simulating random binary sequences with fixed marginal distributions and specified degrees of association between the variables. This last phrase is interpreted in two different ways and simulation methods appropriate to both are described.

Keywords

This publication has 11 references indexed in Scilit:

A Method for Generating High-Dimensional Multivariate Binary Variates
The American Statistician, 1991
Models for Longitudinal Data: A Generalized Estimating Equation Approach
Published by JSTOR ,1988
Frank's family of bivariate distributions
Biometrika, 1987
The Joy of Copulas: Bivariate Distributions with Uniform Marginals
The American Statistician, 1986
Copules archimédiennes et families de lois bidimensionnelles dont les marges sont données
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, 1986
Longitudinal Data Analysis for Discrete and Continuous Outcomes
Published by JSTOR ,1986
Non-Uniform Random Variate Generation
Published by Springer Nature ,1986
Longitudinal data analysis using generalized linear models
Biometrika, 1986
On the foundations of combinatorial theory I. Theory of M bius Functions
Probability Theory and Related Fields, 1964