Methods for Generating Longitudinally Correlated Binary Data

The analysis of longitudinally correlated binary data has attracted considerable attention of late. Since the estimation of parameters in models for such data is based on asymptotic theory, it is necessary to investigate the small-sample properties of estimators by simulation. In this paper, we review the mechanisms that have been proposed for generating longitudinally correlated binary data. We compare and contrast these models with regard to various features, including computational efficiency, flexibility and the range restrictions that they impose on the longitudinal association parameters. Some extensions to the data generation mechanism originally suggested by Kanter (1975) are proposed. Copyright 2007 The Authors. Journal compilation (c) 2007 International Statistical Institute.

[1]  Sin-Ho Jung,et al.  Generating Correlated Binary Variables with Complete Specification of the Joint Distribution , 2001 .

[2]  A. D. Lunn,et al.  A note on generating correlated binary variables , 1998 .

[3]  B. Sutradhar,et al.  Analyzing multivariate longitudinal binary data: A generalized estimating equations approach , 2004 .

[4]  B. Sutradhar.  An Overview on Regression Models for Discrete Longitudinal Responses , 2003 .

[5]  N. Laird,et al.  A likelihood-based method for analysing longitudinal binary responses , 1993 .

[6]  Kalyan Das,et al.  Miscellanea. On the efficiency of regression estimators in generalised linear models for longitudinal data , 1999 .

[7]  Ed Mckenzie.  Extending the correlation structure of exponential autoregressive–moving-average processes , 1981 .

[8]  N. Rao Chaganty,et al.  Efficiency of generalized estimating equations for binary responses , 2004 .

[9]  D. Dockery,et al.  Passive smoking, gas cooking, and respiratory health of children living in six cities. , 2015, The American review of respiratory disease.

[10]  N. Rao Chaganty,et al.  Analysis of Serially Correlated Data Using Quasi-Least Squares , 1998 .

[11]  Brajendra C. Sutradhar,et al.  A non-linear conditional probability model for generating correlated binary data , 2006 .

[12]  C. Park,et al.  A Simple Method for Generating Correlated Binary Variates , 1996 .

[13]  Bahjat F. Qaqish,et al.  A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations , 2003 .

[14]  David M. Zucker,et al.  Modelling and generating correlated binary variables , 2001 .

[15]  S. Gange.  Generating Multivariate Categorical Variates Using the Iterative Proportional Fitting Algorithm , 1995 .

[16]  Alan J. Lee,et al.  Generating Random Binary Deviates Having Fixed Marginal Distributions and Specified Degrees of Association , 1993 .

[17]  Marek Kanter.  Autoregression for discrete processes mod 2 , 1975 .

[18]  M. Piedmonte,et al.  A Method for Generating High-Dimensional Multivariate Binary Variates , 1991 .

[19]  A. Sashegyi,et al.  Estimation in an empirical bayes model for longitudinal and cross‐sectionally clustered binary data , 2000 .