Generating correlated binary variables with complete specification of the joint distribution

被引：0
|
作者：
Kang, SH
Jung, SH
机构：
[1] Ewha Womans Univ, Dept Stat, Seoul 120750, South Korea
[2] Indiana Univ, Sch Med, Div Biostat, Indianapolis, IN 46202 USA
来源：
BIOMETRICAL JOURNAL | 2001年 / 43卷 / 03期
关键词：
generalized estimating equations; ophthalmology; dependence; exchangeable binary data; toxicology;
D O I：
10.1002/1521-4036(200106)43:3<263::AID-BIMJ263>3.0.CO;2-5
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Most statistical methods for the analysis of correlated binary data are based on asymptotic theory. Therefore it is important re, generate correlated binary data efficiently for Monte Carlo simulation studies to investigate the finite sample performance of these methods. This article provides a simple method for generating correlated binary data with a given joint distribution. The key idea is to consider k-variate binary data as a multinomial distribution with 2(k) possible outcomes.
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页码：263 / 269
页数：7
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