Overdispersion and poisson regression
Overdispersion and poisson regression
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DOI：
10.1007/s10940-008-9048-4
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发表时间：
2008-09-01
影响因子：
3.6
通讯作者：
MacDonald, John M.
中科院分区：
文献类型：
--
作者：
Berk, Richard;MacDonald, John M.
本文讨论了计数数据的回归模型的使用。在犯罪学应用中，当计数响应变量存在过度分散的证据时，通常会提出负二项分布是选择的条件分布。有些人继续断言，当使用负二项分布而不是更传统的泊松分布时，过度分散的问题可以“解决”。在本文中，我们回顾了这两种分布所需的假设，并表明只有在非常特殊的情况下，这些说法是真的。
This article discusses the use of regression models for count data. A claim is often made in criminology applications that the negative binomial distribution is the conditional distribution of choice when for a count response variable there is evidence of overdispersion. Some go on to assert that the overdisperson problem can be "solved" when the negative binomial distribution is used instead of the more conventional Poisson distribution. In this paper, we review the assumptions required for both distributions and show that only under very special circumstances are these claims true.