A Simple Method for Generating Correlated Binary Variates
作者:
ChulGyu Park,
Taesung Park,
DongWan Shin,
期刊:
The American Statistician
(Taylor Available online 1996)
卷期:
Volume 50,
issue 4
页码: 306-310
ISSN:0003-1305
年代: 1996
DOI:10.1080/00031305.1996.10473557
出版商: Taylor & Francis Group
关键词: Generalized estimating equations;Poisson variables;Random number generation.
数据来源: Taylor
摘要:
Correlated binary data are frequently analyzed in studies of repeated measurements, reliability analysis, and others. In such studies correlations among binary variables are usually nonnegative. This article provides a simple algorithm for generating an arbitrary dimensional random vector of non-negatively correlated binary variables. In some frequently encountered situations the algorithm reduces to explicit expressions. The correlated binary variables are generated from correlated Poisson variables. The key idea lies in the property that any Poisson random variable can be expressed as a convolution of other independent Poisson random variables. The binary variables have desired correlations by sharing common independent Poisson variables.
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