Intra-cluster correlation as serial vs. equicorrelation in a hierarchical linear model
This paper proposes a simple hierarchical model and a testing strategy to identify intra-cluster correlations. Intra-group correlations are modeled as a combination of nested random effects and serially correlated error components in a hierarchical model. A Neyman C(α) framework is used to derive LM...
| Autores principales: | , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2015
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/170216 |
| Aporte de: |
| Sumario: | This paper proposes a simple hierarchical model and a testing strategy to identify intra-cluster correlations. Intra-group correlations are modeled as a combination of nested random effects and serially correlated error components in a hierarchical model. A Neyman C(α) framework is used to derive LM-type tests to identify the appropriate level of clustering and the type of intra-group correlation. |
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