Multivariate generalized linear models using R

Sebnem Er

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Multivariate generalized linear models using R

机译：使用R的多元广义线性模型

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Generalised linear models (GLMs) represent a class of models for continuous, binary, ordinal and count data types where all observations are independent of each other. In real-life examples with large and complex data sets, we come across multi-level or hierarchical data in which observations are nested in one or more higher levels causing dependence between each other. Since using GLMs when there is dependence between observations on the same unit is not appropriate, generalised linear mixed models have been developed to deal with this correlated data structure. As a result, mixed models are one of the most important statistical models to analyse large and complex data sets with these properties.

机译：广义线性模型（GLM）代表一类用于连续，二进制，有序和计数数据类型的模型，其中所有观测值彼此独立。在具有大型和复杂数据集的现实示例中，我们遇到了多级或分层数据，其中观测值嵌套在一个或多个更高级别中，从而导致彼此之间的依赖性。由于使用GLM不适用于对同一单位的观测值之间的依赖关系，因此已经开发了广义线性混合模型来处理这种相关的数据结构。因此，混合模型是分析具有这些属性的大型和复杂数据集的最重要的统计模型之一。

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《Journal of applied statistics》 |2012年第8期|p.1851|共1页
作者
Sebnem Er;
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Istanbul University, Turkey;

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Multivariate generalized linear models using R

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