INFORMATION

Psicothema was founded in Asturias (northern Spain) in 1989, and is published jointly by the Psychology Faculty of the University of Oviedo and the Psychological Association of the Principality of Asturias (Colegio Oficial de Psicólogos del Principado de Asturias).
We currently publish four issues per year, which accounts for some 100 articles annually. We admit work from both the basic and applied research fields, and from all areas of Psychology, all manuscripts being anonymously reviewed prior to publication.

PSICOTHEMA
  • Director: Laura E. Gómez Sánchez
  • Frequency:
         February | May | August | November
  • ISSN: 0214-9915
  • Digital Edition:: 1886-144X
CONTACT US
  • Address: Ildelfonso Sánchez del Río, 4, 1º B
    33001 Oviedo (Spain)
  • Phone: 985 285 778
  • Fax: 985 281 374
  • Email:psicothema@cop.es

Psicothema, 2008. Vol. Vol. 20 (nº 4). 830-838




Construcción de modelos jerárquicos en contextos aplicados

Guillermo Vallejo Seco, Jaime Arnau Grass* y Roser Bono Cabré*

Universidad de Oviedo y * Universidad de Barcelona

Los modelos lineales jerárquicos se han convertido en una herramienta muy popular para analizar datos que presentan una estructura jerarquizada. Esta metodología reconoce la estructura anidada de los datos y permiten obtener estimaciones insesgadas de las variaciones acaecidas en los distintos niveles de la jerarquía. El objetivo de este artículo es ilustrar la construcción de modelos jerárquicos en contextos transversales y longitudinales implicando tres y cuatro niveles, respectivamente. Para mostrar el proceso de modelado estadístico se evalúa la eficacia de un programa de intervención diseñado para incrementar el rendimiento matemático de estudiantes de Primaria. El ejemplo empleado se analiza con los paquetes estadísticos SAS y SPSS, cuya sintaxis se detalla convenientemente en el manuscrito.

Construction of hierarchical models in applied contexts. Hierarchical linear models have become a very popular tool for analyzing data with a hierarchical structure. This methodology recognizes the nested structure of the data and allows obtaining unbiased estimates of the variations found in the different levels of the hierarchy. The goal of this article is to illustrate the construction of hierarchical models both in cross-sectional and longitudinal contexts involving three and four levels, respectively. The efficiency of an intervention program designed to improve the mathematical performance of primary school students is evaluated to illustrate the statistical modelling process. The example used is analyzed by the SAS and SPSS packages, whose syntax is duly detailed in the manuscript.

PDF

Impact factor 2022:  JCR WOS 2022:  FI = 3.6 (Q2);  JCI = 1.21 (Q1) / SCOPUS 2022:  SJR = 1.097;  CiteScore = 6.4 (Q1)