Analysis of count data with covariate dependence in both mean and variance
Analysis of count data with covariate dependence in both mean and variance
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DOI：
10.1080/02664763.2011.567250
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发表时间：
2011-01-01
影响因子：
1.5
通讯作者：
Smith, D. M.
中科院分区：
文献类型：
--
作者：
Faddy, M. J.;Smith, D. M.
广义扩展泊松过程建模允许协变量依赖的分散以及协变量依赖的平均响应。这是通过使用均值和方差的近似表达式的重新参数化来完成的。这种建模允许在同一建模框架内容纳同一数据集中的分散不足和分散过度或两者的结合。所有必要的计算都可以用数字来完成，从而能够对所有模型参数进行最大似然估计。该模型被应用于重新分析两个已公布的数据集，其中有证据表明协变量依赖的分散，与模型导致这些数据的更翔实的分析和更适当的措施的任何估计的精度。
Extended Poisson process modelling is generalised to allow for covariate-dependent dispersion as well as a covariate-dependent mean response. This is done by a re-parameterisation that uses approximate expressions for the mean and variance. Such modelling allows under-and over-dispersion, or a combination of both, in the same data set to be accommodated within the same modelling framework. All the necessary calculations can be done numerically, enabling maximum likelihood estimation of all model parameters to be carried out. The modelling is applied to re-analyse two published data sets, where there is evidence of covariate-dependent dispersion, with the modelling leading to more informative analyses of these data and more appropriate measures of the precision of any estimates.