Artículo
Hierarchical linear mixed models in multi-stage sampling soil studies
Fecha de publicación:
08/2012
Editorial:
Springer
Revista:
Environmental And Ecological Statistics
ISSN:
1352-8505
e-ISSN:
1573-3009
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The issue of variances of different soil variables prevailing at different sampling scales is addressed. This topic is relevant for soil science, agronomy and landscape ecology. In multi-stage sampling there are randomness components in each stage of sampling which can be taken into account by introducing random effects in analysis through the use of hierarchical linear mixed models (HLMM). Due to the nested sampling scheme, there are several hierarchical sub-models. The selection of the best model can be carried out through likelihood ratio tests (LRTs) or Wald tests, which are asymptotically equivalent under standard conditions. However, when the comparison leads to a restricted hypothesis of variance components, standard conditions are not maintained, which leads to more elaborated versions of LRTs. These versions are not disseminated among environmental scientists. The present study shows the modeling of soil data from a sampling where sites, fields within sites, transects within fields, and sampling points within transects were selected in order to take samples from different vegetation types (open and shade). For soil data, several sub-models were compared using Wald tests, classic LRTs and adjusted LRTs where the distribution of the test statistic under the null hypothesis is the Chi-square mixture of Chi-square distributions. The inclusion of random effects via HLMM and suggested by the latest version of LRT allowed us to detect effects of vegetation type on soil properties that were not detected under a classical ANOVA.
Palabras clave:
Bulk Density
,
Likelihood Ratio Test (Lrt)
,
Texture
,
Total Organic Carbon
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos(CCT - CORDOBA)
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - CORDOBA
Articulos de CTRO.CIENTIFICO TECNOL.CONICET - CORDOBA
Citación
Gili, Adriana Anahi; Noellemeyer, Elke Johanna; Balzarini, Monica Graciela; Hierarchical linear mixed models in multi-stage sampling soil studies; Springer; Environmental And Ecological Statistics; 20; 2; 8-2012; 237-252
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